@inproceedings{ellison_robust_2025,
	title = {Robust {V2X} {Cruise} {Control} for {Class} 8 {Trucks} in the {Presence} of {Traffic} {Lights}},
	url = {https://saemobilus.sae.org/papers/robust-v2x-cruise-control-class-8-trucks-presence-traffic-lights-2025-01-8033},
	doi = {10.4271/2025-01-8033},
	abstract = {An implementation of a robust predictive cruise control method for class 8 trucks utilizing V2X communication with connected traffic lights is presented in this work. This method accounts for traffic signal phases with the goal of reducing energy consumption when possible while respecting safety concerns. Tightened constraints are created using a robust model predictive control (RMPC) framework in which constraints are modified so that the safety critical requirements are satisfied even in the presence of disturbances, while requiring only the expected bounds of the disturbances to be provided. In particular, variation in the actuator performance under different conditions presents a unique challenge for this application, which the approach applied in this work is well-suited to handle. The errors resulting from lower-level control and actuator performance are accounted for by treating them as bounded and additive disturbances on the states of the model used in the higher level MPC, and the RMPC method is demonstrated to satisfy constraints in the presence of arbitrary bounded disturbances that can be modeled in this way. Simulation results show that these tightened constraints successfully account for error due to low-level control and actuator performance for class 8 trucks. Furthermore, tests were performed on hardware which show the capability for real-time application.},
	publisher = {SAE International},
	author = {Ellison, Evan and Ward, Jacob and Brown, Lowell and Bevly, David},
	month = mar,
	year = {2025},
}

An implementation of a robust predictive cruise control method for class 8 trucks utilizing V2X communication with connected traffic lights is presented in this work. This method accounts for traffic signal phases with the goal of reducing energy consumption when possible while respecting safety concerns. Tightened constraints are created using a robust model predictive control (RMPC) framework in which constraints are modified so that the safety critical requirements are satisfied even in the presence of disturbances, while requiring only the expected bounds of the disturbances to be provided. In particular, variation in the actuator performance under different conditions presents a unique challenge for this application, which the approach applied in this work is well-suited to handle. The errors resulting from lower-level control and actuator performance are accounted for by treating them as bounded and additive disturbances on the states of the model used in the higher level MPC, and the RMPC method is demonstrated to satisfy constraints in the presence of arbitrary bounded disturbances that can be modeled in this way. Simulation results show that these tightened constraints successfully account for error due to low-level control and actuator performance for class 8 trucks. Furthermore, tests were performed on hardware which show the capability for real-time application.

@inproceedings{flegel_monocular_2025,
	title = {Monocular {3D} {Pedestrian} {Detection} and {Tracking} {With} {Neural} {Network} with {Uncertainty} {Estimate} for {Safe} {Drone} {Operation}},
	url = {https://doi.org/10.2514/6.2025-2117},
	abstract = {In order for drone use to become more integrated in daily life, drones need to be able to accurately detect and localize humans in their surroundings. We propose a solution to this problem using a monocular camera. A notable feature of the proposed algorithm is its independence from joint detection or depth estimation algorithms, which are more computationally complex. These features make it particularly suited for embedded systems and robotics applications on resource-constrained platforms, including drones. In particular, a neural network based approach is utilized to accurately detect and localize humans by estimating their relative position, and velocity, as well as an associated uncertainty of the estimates. Our results indicate that the position estimate is comparable to other methods in the literature, despite being a lighter weight algorithm, with the velocity estimates showing the overall velocity trend, but requiring further improvements with respect to accuracy.},
	author = {Flegel, Tyler and {Praveen Jawaharlal Ayyanathan} and {Ehsan Taheri} and Bevly, David},
	month = jan,
	year = {2025},
}

In order for drone use to become more integrated in daily life, drones need to be able to accurately detect and localize humans in their surroundings. We propose a solution to this problem using a monocular camera. A notable feature of the proposed algorithm is its independence from joint detection or depth estimation algorithms, which are more computationally complex. These features make it particularly suited for embedded systems and robotics applications on resource-constrained platforms, including drones. In particular, a neural network based approach is utilized to accurately detect and localize humans by estimating their relative position, and velocity, as well as an associated uncertainty of the estimates. Our results indicate that the position estimate is comparable to other methods in the literature, despite being a lighter weight algorithm, with the velocity estimates showing the overall velocity trend, but requiring further improvements with respect to accuracy.

@inproceedings{ward_tractor-trailer_2025,
	title = {Tractor-{Trailer} {Vehicle} {Rollover} {Avoidance} {Using} {Chance}-{Constrained} {Reference} {Governor} and {Data}-{Driven} {Ultra}-{Local} {Model}},
	url = {https://www.sciencedirect.com/science/article/pii/S2405896325001314?via%3Dihub},
	abstract = {This work presents a novel method for preventing tractor-trailer rollovers through the use of a chance-constrained reference governor and a data-driven ultra-local model. Typical commercial rollover prevention systems function by adding a system that interfaces with the trailer brakes and is capable of measuring the lateral acceleration of the trailer. If certain lateral acceleration thresholds are exceeded the trailer brakes will activate to reduce the speed of the tractor-trailer system. The system proposed in this work assumes that the truck is semi-autonomous and following a path generated by some high-level path planner. Rollover avoidance is then achieved by minimally modifying the reference path to ensure that a prescribed lateral acceleration threshold is not exceeded through the use of a reference governor. Because, in a realistic system, stochastic disturbances such as estimation errors or wind disturbances exist and since an analytical model of the truck is likely unknown, a data-driven model is leveraged along with a chance-constrained formulation of the reference governor. This chance-constrained reference governor is demonstrated to successfully constrain the tractor-trailer lateral acceleration below a prescribed threshold with a probability β.},
	language = {en},
	author = {Ward, Jacob and Li, Nan and Bevly, David and Brown, Lowell},
	month = jan,
	year = {2025},
}

This work presents a novel method for preventing tractor-trailer rollovers through the use of a chance-constrained reference governor and a data-driven ultra-local model. Typical commercial rollover prevention systems function by adding a system that interfaces with the trailer brakes and is capable of measuring the lateral acceleration of the trailer. If certain lateral acceleration thresholds are exceeded the trailer brakes will activate to reduce the speed of the tractor-trailer system. The system proposed in this work assumes that the truck is semi-autonomous and following a path generated by some high-level path planner. Rollover avoidance is then achieved by minimally modifying the reference path to ensure that a prescribed lateral acceleration threshold is not exceeded through the use of a reference governor. Because, in a realistic system, stochastic disturbances such as estimation errors or wind disturbances exist and since an analytical model of the truck is likely unknown, a data-driven model is leveraged along with a chance-constrained formulation of the reference governor. This chance-constrained reference governor is demonstrated to successfully constrain the tractor-trailer lateral acceleration below a prescribed threshold with a probability β.

@unpublished{schretter_estimation_2024,
	title = {Estimation of {Relative} {Motion} between {Non}-{Rigid} {Bodies} on a {Semi}-{Truck}},
	url = {https://etd.auburn.edu//handle/10415/9118},
	abstract = {This thesis develops methods to estimate the relative motion between the cabin and chassis
of a semi-truck without the use of a complex suspension model between the two bodies. In,
this thesis only sensors that would be already available on current vehicle using both inertial
and GPS sensors on the cabin and chassis bodies are utilized. Automation of Semi-Trucks
requires perceiving obstacles that are both stationary and moving that exist close to the truck.
The cabin and chassis of a truck have a suspension system between them. This can cause there
to be offsets between the perception of obstacles from the cabin vs the chassis which can inhibit
autonomy of the vehicle.
The thesis analyzes both the use of GPS/INS integration as well as Transfer Alignment
techniques to correct an IMU mounted on the chassis with measurements taken from GPS an tennas and IMUs mounted on the cabin. Additional methods are investigated to further improve
these techniques such as taking into account the quality of the cabin measurements, adding
higher fidelity models for state estimates, or reducing the amount of states. Using real world
datasets, the methods are evaluated by comparing the corrected chassis solution to a high qual ity GPS/INS senor that acts as a truth measurement. The results show that the relative motion
between the two bodies can be determined. The quality of the final solution is dependent on
the performance of both the cabin solution and chassis IMU. The thesis will show with a high
quality cabin GPS/INS solution the chassis attitude solution can be found to be within 0.5
degrees of the true value.},
	language = {en},
	urldate = {2024-06-25},
	author = {Schretter, Brendan},
	month = jan,
	year = {2024},
	note = {Accepted: 2024-01-08T19:00:34Z},
}

This thesis develops methods to estimate the relative motion between the cabin and chassis of a semi-truck without the use of a complex suspension model between the two bodies. In, this thesis only sensors that would be already available on current vehicle using both inertial and GPS sensors on the cabin and chassis bodies are utilized. Automation of Semi-Trucks requires perceiving obstacles that are both stationary and moving that exist close to the truck. The cabin and chassis of a truck have a suspension system between them. This can cause there to be offsets between the perception of obstacles from the cabin vs the chassis which can inhibit autonomy of the vehicle. The thesis analyzes both the use of GPS/INS integration as well as Transfer Alignment techniques to correct an IMU mounted on the chassis with measurements taken from GPS an tennas and IMUs mounted on the cabin. Additional methods are investigated to further improve these techniques such as taking into account the quality of the cabin measurements, adding higher fidelity models for state estimates, or reducing the amount of states. Using real world datasets, the methods are evaluated by comparing the corrected chassis solution to a high qual ity GPS/INS senor that acts as a truth measurement. The results show that the relative motion between the two bodies can be determined. The quality of the final solution is dependent on the performance of both the cabin solution and chassis IMU. The thesis will show with a high quality cabin GPS/INS solution the chassis attitude solution can be found to be within 0.5 degrees of the true value.

@unpublished{miller_deep_2024,
	title = {Deep {Integration} of a {Flight} {Vehicle} {Dynamic} {Model} in a {Vector} {Tracking} {Software} {Defined} {Receiver}},
	url = {https://etd.auburn.edu//handle/10415/9117},
	abstract = {The greater occurrence of signal interference on Global Navigation Satellite Systems
(GNSS) requires additional alternative navigation solutions to provide robust, reliable localization
of flight vehicles when measurements from GNSS are unavailable. This thesis proposes a
Flight Vehicle Dynamic Model (FVDM) that is deeply integrated with Global Positioning System
(GPS) correlator measurements for aircraft state estimates in GPS-challenged environments.
It is well-documented that large, modern aircraft feature an array of sensors that work in
tandem to provide robust positioning performance. However, the sizing limitations of low Size,
Weight, Power, and Cost (SWaP-C) do not allow for such redundant sensor suites, meaning
an alternative navigation solution is required. Furthermore, low cost flight vehicles typically
feature lower quality sensors that are subject to vibrations and subsequently faulty, unreliable
measurements that provide no benefit to the flight vehicle when GNSS measurements are also
considered unreliable.
The FVDM is a high-fidelity flight vehicle model based on the Diamond DA-40 singlepropeller
fixed wing aircraft. The aircraft model features a piston engine model that generates
thrust power through a shaft that spins a numerically modeled 3-blade propeller. The speed of
the propeller is controlled through a electric governor, and the pitch is controlled to maintain
efficient propeller action onto the incident airflow. The aerodynamics of the aircraft are modeled
using a discretized aerodynamic coefficient technique, also known as strip theory. Although not
used in this work, a landing gear model incorporates the three landing gear on the Diamond
DA-40 and evaluates the forces and moments applied during landing as a second-order springmass-
damper system. An International Standard Atmosphere (ISA) model is used to calculate
the density, temperature, and ambient pressure based on aircraft altitude. To close the loop of
the FVDM, a set of controllers in collaboration with a waypoint manager are used to actuate the
control surfaces on the aircraft. Multiple planned paths are demonstrated during this work and
are presented in their respective sections.
The proposed navigation filter presented in this work provides a closed loop solution fusion
of the vector tracking loop algorithms and the FVDM process model via a Vector Delay and
Frequency Lock Loop (VDFLL). Vector tracking loops are able to maintain channel lock on
satellite signals when either signal interference is present, or the dynamics of the collection
platform are too high for scalar loops to track the signal consistently.
The results within this work showcase the improvements in flight vehicle state estimates
when compared to a standard VDFLL zero-mean acceleration kinematic model. In simulation,
two trajectories are flown under varying levels of signal degradation. The first trajectory is
a steady-level, un-accelerated flight path where the aircraft is maintaining a constant altitude
and heading for the duration of the 60 second simulation. For this trajectory, it is expected
that the standard VDFLL implementation performs comparably to the proposed navigation
filter. The second trajectory features a more dramatic flight bath – full of oscillatory turns and a
constant climb segments. For the second trajectory, the proposed navigation filter out performs
the standard VDFLL due to its capability to predict the behavior of the aircraft given a set of
control inputs. Each of the trajectories and subsequent cases of signal degradation are tested in
100-run Monte-Carlo sims to further test the robustness of the proposed navigation filter.},
	language = {en},
	urldate = {2024-06-25},
	author = {Miller, Noah},
	month = jan,
	year = {2024},
	note = {Accepted: 2024-01-04T16:54:42Z},
}

The greater occurrence of signal interference on Global Navigation Satellite Systems (GNSS) requires additional alternative navigation solutions to provide robust, reliable localization of flight vehicles when measurements from GNSS are unavailable. This thesis proposes a Flight Vehicle Dynamic Model (FVDM) that is deeply integrated with Global Positioning System (GPS) correlator measurements for aircraft state estimates in GPS-challenged environments. It is well-documented that large, modern aircraft feature an array of sensors that work in tandem to provide robust positioning performance. However, the sizing limitations of low Size, Weight, Power, and Cost (SWaP-C) do not allow for such redundant sensor suites, meaning an alternative navigation solution is required. Furthermore, low cost flight vehicles typically feature lower quality sensors that are subject to vibrations and subsequently faulty, unreliable measurements that provide no benefit to the flight vehicle when GNSS measurements are also considered unreliable. The FVDM is a high-fidelity flight vehicle model based on the Diamond DA-40 singlepropeller fixed wing aircraft. The aircraft model features a piston engine model that generates thrust power through a shaft that spins a numerically modeled 3-blade propeller. The speed of the propeller is controlled through a electric governor, and the pitch is controlled to maintain efficient propeller action onto the incident airflow. The aerodynamics of the aircraft are modeled using a discretized aerodynamic coefficient technique, also known as strip theory. Although not used in this work, a landing gear model incorporates the three landing gear on the Diamond DA-40 and evaluates the forces and moments applied during landing as a second-order springmass- damper system. An International Standard Atmosphere (ISA) model is used to calculate the density, temperature, and ambient pressure based on aircraft altitude. To close the loop of the FVDM, a set of controllers in collaboration with a waypoint manager are used to actuate the control surfaces on the aircraft. Multiple planned paths are demonstrated during this work and are presented in their respective sections. The proposed navigation filter presented in this work provides a closed loop solution fusion of the vector tracking loop algorithms and the FVDM process model via a Vector Delay and Frequency Lock Loop (VDFLL). Vector tracking loops are able to maintain channel lock on satellite signals when either signal interference is present, or the dynamics of the collection platform are too high for scalar loops to track the signal consistently. The results within this work showcase the improvements in flight vehicle state estimates when compared to a standard VDFLL zero-mean acceleration kinematic model. In simulation, two trajectories are flown under varying levels of signal degradation. The first trajectory is a steady-level, un-accelerated flight path where the aircraft is maintaining a constant altitude and heading for the duration of the 60 second simulation. For this trajectory, it is expected that the standard VDFLL implementation performs comparably to the proposed navigation filter. The second trajectory features a more dramatic flight bath – full of oscillatory turns and a constant climb segments. For the second trajectory, the proposed navigation filter out performs the standard VDFLL due to its capability to predict the behavior of the aircraft given a set of control inputs. Each of the trajectories and subsequent cases of signal degradation are tested in 100-run Monte-Carlo sims to further test the robustness of the proposed navigation filter.

@inproceedings{bentley_expanding_2024,
	title = {Expanding the {Use} of {Vehicle} {Specific} {Power} in {Analysis} of {Platoon} {Performance}},
	url = {https://www.sae.org/publications/technical-papers/content/2024-01-2057/},
	abstract = {Platooning is a coordinated driving strategy by which following trucks are placed into the wake of leading vehicles. Doing this leads to two primary benefits. First, the vehicles following are shielded from aerodynamic drag by a “pulling” effect. Secondly, by placing vehicles behind the leading truc},
	language = {English},
	urldate = {2024-06-20},
	author = {Bentley, John and Stegner, Evan and Bevly, David M. and Hoffman, Mark},
	month = apr,
	year = {2024},
	doi = {10.4271/2024-01-2057},
}

Platooning is a coordinated driving strategy by which following trucks are placed into the wake of leading vehicles. Doing this leads to two primary benefits. First, the vehicles following are shielded from aerodynamic drag by a “pulling” effect. Secondly, by placing vehicles behind the leading truc

@inproceedings{baker_performance_2024,
	title = {Performance {Evaluation} of {Direct} {Position} {Estimation} in {High}-{Dynamic} {GPS} {Environments}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=19654},
	doi = {10.33012/2024.19654},
	abstract = {Satellite systems purpose-built for navigation are increasingly common and continually updated for greater accuracy and integrity; however, receivers are not always so robust. When receiver dynamics contain significant higher order terms, typical signal tracking procedures will begin to fail. This work considers the use of Direct Position Estimation (DPE) to confront this problem. DPE is a method of obtaining position, velocity, and time estimates from global navigation satellite systems by directly evaluating an objective function with the state vector. Though DPE has the potential for solutions with higher accuracy, it requires significantly more comutations. This work considers evaluating the effectiveness of using a constant-velocity model with shorter correlation periods to maintain accurate position solutions from GPS LNAV signals. Results include the MonteCarlo position RMSE from a signal-level simulation for scenarios varing in acceleration magnitude, signal power, and the chosen correlation period length. Additionally, these results are compared to the use of DPE with a state vector extended to include acceleration. Results show that the constant velocity assumption would be sufficient for most common scenarios if an optimal correlation period is chosen. Additionally, a higher-order representation of receiver dynamics is not needed unless experiencing high-dynamic scenarios with sufficiently low power.},
	language = {en},
	urldate = {2024-06-20},
	author = {Baker, Blake and Givhan, Anderson and Martin, Scott},
	month = apr,
	year = {2024},
	pages = {406--416},
}

Satellite systems purpose-built for navigation are increasingly common and continually updated for greater accuracy and integrity; however, receivers are not always so robust. When receiver dynamics contain significant higher order terms, typical signal tracking procedures will begin to fail. This work considers the use of Direct Position Estimation (DPE) to confront this problem. DPE is a method of obtaining position, velocity, and time estimates from global navigation satellite systems by directly evaluating an objective function with the state vector. Though DPE has the potential for solutions with higher accuracy, it requires significantly more comutations. This work considers evaluating the effectiveness of using a constant-velocity model with shorter correlation periods to maintain accurate position solutions from GPS LNAV signals. Results include the MonteCarlo position RMSE from a signal-level simulation for scenarios varing in acceleration magnitude, signal power, and the chosen correlation period length. Additionally, these results are compared to the use of DPE with a state vector extended to include acceleration. Results show that the constant velocity assumption would be sufficient for most common scenarios if an optimal correlation period is chosen. Additionally, a higher-order representation of receiver dynamics is not needed unless experiencing high-dynamic scenarios with sufficiently low power.

@inproceedings{sturdivant_buoys_2024,
	title = {Buoys as {Maritime} {Signals} of {Opportunity}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=19640},
	doi = {10.33012/2024.19640},
	abstract = {Buoys have been a long-standing source of position and guidance information with usage dating all the way back to the 13th century. While not traditionally designed for navigation, this paper proposes the idea of exploiting modern buoys as a signal of opportunity (SOOP). The goal is to present the efficacy of buoys as compared to other accepted constellations, namely low Earth orbit satellites (LEO). Similar to cellular or radio towers, they are terrestrial emitters that would provide observability overseas. Global DOP analyses are performed to snapshot buoy availability and assess the capability of a buoy-based navigator with respect to the buoy location. A Doppler-INS, tightly-coupled, extended Kalman filter (EKF) model is developed and presented with the navigation performance being assessed by Monte Carlo simulations. When considering a simulation with adequate dilution of precision (DOP) estimates for the buoy constellation, it is found that buoy-based navigator performs comparably to LEO-based SOOP navigator.},
	language = {en},
	urldate = {2024-06-20},
	author = {Sturdivant, Daniel F. and Martin, Scott M.},
	month = apr,
	year = {2024},
	pages = {182--194},
}

Buoys have been a long-standing source of position and guidance information with usage dating all the way back to the 13th century. While not traditionally designed for navigation, this paper proposes the idea of exploiting modern buoys as a signal of opportunity (SOOP). The goal is to present the efficacy of buoys as compared to other accepted constellations, namely low Earth orbit satellites (LEO). Similar to cellular or radio towers, they are terrestrial emitters that would provide observability overseas. Global DOP analyses are performed to snapshot buoy availability and assess the capability of a buoy-based navigator with respect to the buoy location. A Doppler-INS, tightly-coupled, extended Kalman filter (EKF) model is developed and presented with the navigation performance being assessed by Monte Carlo simulations. When considering a simulation with adequate dilution of precision (DOP) estimates for the buoy constellation, it is found that buoy-based navigator performs comparably to LEO-based SOOP navigator.

@inproceedings{boyd_meeting_2024,
	title = {Meeting {Modern} {Timing} {Demands} with {LEO} {Satellite} {Signals} and {Long} {Baseline} {Phase} {Interferometry}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=19610},
	doi = {10.33012/2024.19610},
	abstract = {A method for estimating a receiver’s clock bias and drift during a Global Navigation Satellite System (GNSS) outage is presented. This method is based on an interferometric receiver that uses observables from Low Earth Orbit (LEO) satellite vehicles (SVs) to estimate SV position and user clock bias. The interferometric receiver at a known location differences LEO measurements across multiple antennas to provide Angle of Arrival (AoA) estimates for SVs, as well as non-cooperative pseudoranges for state estimation. A complete measurement model for the system is developed and presented. Clock estimation performance of the receiver is assessed through Monte Carlo simulations, where the varied parameters are baseline length of the antenna array, carrier to noise density ratio (C/N0) of the received signal, and quality of oscillator used by the receiver. Using an antenna spacing of 20 meters, an equipped OCXO, and assuming a C/N0 of 85 dB-Hz, it is found that the receiver maintains sufficient timing accuracy to meet various modern timing demands, namely, 1us accuracy.},
	language = {en},
	urldate = {2024-06-20},
	author = {Boyd, Landon and Bevly, David M.},
	month = apr,
	year = {2024},
	pages = {293--304},
}

A method for estimating a receiver’s clock bias and drift during a Global Navigation Satellite System (GNSS) outage is presented. This method is based on an interferometric receiver that uses observables from Low Earth Orbit (LEO) satellite vehicles (SVs) to estimate SV position and user clock bias. The interferometric receiver at a known location differences LEO measurements across multiple antennas to provide Angle of Arrival (AoA) estimates for SVs, as well as non-cooperative pseudoranges for state estimation. A complete measurement model for the system is developed and presented. Clock estimation performance of the receiver is assessed through Monte Carlo simulations, where the varied parameters are baseline length of the antenna array, carrier to noise density ratio (C/N0) of the received signal, and quality of oscillator used by the receiver. Using an antenna spacing of 20 meters, an equipped OCXO, and assuming a C/N0 of 85 dB-Hz, it is found that the receiver maintains sufficient timing accuracy to meet various modern timing demands, namely, 1us accuracy.

@inproceedings{givhan_analysis_2024,
	title = {Analysis of a {Vector} {Tracking} {Aided} {Synthetic} {CRPA} for {Spoofing} {Mitigation}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=19629},
	doi = {10.33012/2024.19629},
	abstract = {One of the best methods to detect and mitigate spoofing attacks involves using angle of arrival information from an antenna array; however, due to SWAPc concerns, CRPAs can be costly to field. This work demonstrates the effectiveness of a limited SWAPc CRPA with two elements used in combination with a vector tracking receiver on a moving vehicle to synthesize a larger array for spoofing detection and mitigation. The receiver feeds back navigation information to generate compensated correlations that preserve spatial phase information from the received wave front. These correlations are fed into a MUSIC algorithm to determine angle of arrival for estimating user attitude. The necessity of known navigation information complicates the algorithm when operating in a spoofed environment. To combat this issue, a layered RAIM based algorithm is proposed and tested in a Safran Skydel simulation to show the recoverability of the true solution with a two-element array. First, the receiver tracks all signals in view and provides measurements to a traditional pseudorange RAIM algorithm. The algorithm returns all consistent PVT solution combinations below a threshold; after, all candidate solutions are then used to generate correlations for the MUSIC algorithm. Finally, the angle of arrival information is then used to jointly estimate attitude and determine the spoofed solution by using a secondary RAIM algorithm. The true PVT solution is shown to be recoverable; additionally, the roll, pitch, and yaw are all estimated to within 2 degrees of error. Pointing vectors may also be estimated for spoofer localization.},
	language = {en},
	urldate = {2024-06-20},
	author = {Givhan, C. Anderson and Martin, Scott M.},
	month = apr,
	year = {2024},
	pages = {687--698},
}

One of the best methods to detect and mitigate spoofing attacks involves using angle of arrival information from an antenna array; however, due to SWAPc concerns, CRPAs can be costly to field. This work demonstrates the effectiveness of a limited SWAPc CRPA with two elements used in combination with a vector tracking receiver on a moving vehicle to synthesize a larger array for spoofing detection and mitigation. The receiver feeds back navigation information to generate compensated correlations that preserve spatial phase information from the received wave front. These correlations are fed into a MUSIC algorithm to determine angle of arrival for estimating user attitude. The necessity of known navigation information complicates the algorithm when operating in a spoofed environment. To combat this issue, a layered RAIM based algorithm is proposed and tested in a Safran Skydel simulation to show the recoverability of the true solution with a two-element array. First, the receiver tracks all signals in view and provides measurements to a traditional pseudorange RAIM algorithm. The algorithm returns all consistent PVT solution combinations below a threshold; after, all candidate solutions are then used to generate correlations for the MUSIC algorithm. Finally, the angle of arrival information is then used to jointly estimate attitude and determine the spoofed solution by using a secondary RAIM algorithm. The true PVT solution is shown to be recoverable; additionally, the roll, pitch, and yaw are all estimated to within 2 degrees of error. Pointing vectors may also be estimated for spoofer localization.

@inproceedings{karlins_gnss_2024,
	title = {{GNSS} {Hardware} in the {Loop} {Simulation} for {Autonomous} {Racing} {Localization} {Development}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=19644},
	doi = {10.33012/2024.19644},
	abstract = {Development of any autonomous mobile robot platform will invariably involve various stages of testing individual components, and the full integrated platform. For many autonomous vehicles, a combination of operating cost, platform availability, operational environment, or other logistical constraints makes full scale live testing impractical. Furthermore, even when live testing is possible, test requirements such as high repeatability or introduction of edge cases may not be achievable. Autonomous Racing is a robotics field that acutely struggles from these testing constraints, and as such, various bespoke simulation tools have been developed by research teams studying this area. GNSS based localization algorithms are critical to safe and reliable operation of these vehicles, but are limited in their ability to be tested in simulation due to the difficulty of modeling intricate receiver behaviors in complex scenarios. Component behavior modeling for simulation development can be bypassed by directly including the test hardware in the simulation loop, also known as a Hardware-in-the-Loop simulation. This paper covers the initial design and testing of a GNSS Hardware-in-the-Loop simulation system for autonomous vehicles with a particular focus on autonomous racing. The simulation system is designed as an extension to existing software-in-the-loop simulation tools developed by Autonomous Tiger Racing, a research group competing in the Indy Autonomous Challenge. Preliminary tests and experiments are performed on this nascent system, and current capabilities and outstanding issues are identified.},
	language = {en},
	urldate = {2024-06-20},
	author = {Karlins, Bryce J. and Harris, Jacob W. and Meyer, Stephanie W. and Bevly, David M.},
	month = apr,
	year = {2024},
	pages = {391--401},
}

Development of any autonomous mobile robot platform will invariably involve various stages of testing individual components, and the full integrated platform. For many autonomous vehicles, a combination of operating cost, platform availability, operational environment, or other logistical constraints makes full scale live testing impractical. Furthermore, even when live testing is possible, test requirements such as high repeatability or introduction of edge cases may not be achievable. Autonomous Racing is a robotics field that acutely struggles from these testing constraints, and as such, various bespoke simulation tools have been developed by research teams studying this area. GNSS based localization algorithms are critical to safe and reliable operation of these vehicles, but are limited in their ability to be tested in simulation due to the difficulty of modeling intricate receiver behaviors in complex scenarios. Component behavior modeling for simulation development can be bypassed by directly including the test hardware in the simulation loop, also known as a Hardware-in-the-Loop simulation. This paper covers the initial design and testing of a GNSS Hardware-in-the-Loop simulation system for autonomous vehicles with a particular focus on autonomous racing. The simulation system is designed as an extension to existing software-in-the-loop simulation tools developed by Autonomous Tiger Racing, a research group competing in the Indy Autonomous Challenge. Preliminary tests and experiments are performed on this nascent system, and current capabilities and outstanding issues are identified.

@unpublished{sprunk_utilization_2023,
	title = {The {Utilization} of {Geometric} {Hashing} {Techniques} for {Feature} {Association} during {Ground} {Vehicle} {Localization}},
	url = {https://etd.auburn.edu//handle/10415/8682},
	abstract = {This thesis presents a new approach to laser-based robot localization using the concept of geometric hashing. The technique operates on an a priori feature map representing the navigation environment by recording all possible feature combinations as transformation-invariant sets. Each combination can be defined by an implementation-specific geometric basis, and then hashed in order to promote rapid parallelizable search conditions and easily encode large quantities of information. 

The primary focus of this work is centered on the individual component of map data association within the much larger localization pipeline. At this step, the navigation system is generally required to provide a correct association between features extracted in real-time from the environment and their corresponding a priori mapped counterparts. In addition to the main concerns of accuracy and reliability, this thesis addresses several other relevant challenges present in feature-based localization such as time complexity, sensitivity to noise, and the detection of map symmetries.

The concept of using geometric hashing for laser-based localization consists of three phases: the training phase, screening phase, and recognition phase. Within this work, each phase is thoroughly defined and analyzed. Particular attention is given toward the utilization of cylindrical-like features found predominantly in urban environments for use during localization. A simulation was developed to test and verify geometric hashing localization in both unique and ambiguous environments. The results validated that geometric hashing localization can provide sub-meter level accuracy even in the presence of ambiguous geometries so long as sufficient information is present. To test the approach on time-critical scenarios, an implementation of the data association algorithm written C++ was integrated into an existing localization framework deployed on a vehicle. Results showed that the positioning solution is capable of providing sub-meter accuracy at 20 Hz update rates driving through urban environments.},
	language = {en},
	urldate = {2024-06-25},
	author = {Sprunk, Michael},
	month = apr,
	year = {2023},
	note = {Accepted: 2023-04-28T22:35:44Z},
}

This thesis presents a new approach to laser-based robot localization using the concept of geometric hashing. The technique operates on an a priori feature map representing the navigation environment by recording all possible feature combinations as transformation-invariant sets. Each combination can be defined by an implementation-specific geometric basis, and then hashed in order to promote rapid parallelizable search conditions and easily encode large quantities of information. The primary focus of this work is centered on the individual component of map data association within the much larger localization pipeline. At this step, the navigation system is generally required to provide a correct association between features extracted in real-time from the environment and their corresponding a priori mapped counterparts. In addition to the main concerns of accuracy and reliability, this thesis addresses several other relevant challenges present in feature-based localization such as time complexity, sensitivity to noise, and the detection of map symmetries. The concept of using geometric hashing for laser-based localization consists of three phases: the training phase, screening phase, and recognition phase. Within this work, each phase is thoroughly defined and analyzed. Particular attention is given toward the utilization of cylindrical-like features found predominantly in urban environments for use during localization. A simulation was developed to test and verify geometric hashing localization in both unique and ambiguous environments. The results validated that geometric hashing localization can provide sub-meter level accuracy even in the presence of ambiguous geometries so long as sufficient information is present. To test the approach on time-critical scenarios, an implementation of the data association algorithm written C++ was integrated into an existing localization framework deployed on a vehicle. Results showed that the positioning solution is capable of providing sub-meter accuracy at 20 Hz update rates driving through urban environments.

@unpublished{smith_timing_2023,
	title = {Timing {Evaluation} of {Iridium} {Satellite} {Time} and {Location} {Signal}: {Measurement}-{Level} {Implementation} and {Receiver} {Hardware} {Time} {Interval} {Comparison}},
	shorttitle = {Timing {Evaluation} of {Iridium} {Satellite} {Time} and {Location} {Signal}},
	url = {https://etd.auburn.edu//handle/10415/9082},
	abstract = {This thesis assesses the accuracy, stability, and convergence rates of receiver timing solutions with the Iridium Satellite Time and Location (STL) signal through two studies. In the first experiment, an Extended Kalman Filter (EKF) and a Weighted Least Squares (WLS) solution are used to estimate the clock states of a static receiver at an antenna location which is known and unknown, respectively. In the second experiment, a 1-PPS (Pulse-Per-Second) time interval study is conducted with two, commercially-available Jackson Labs Technologies STL-2600 receivers, which are both provided a precise position. Both tests are conducted using an on-board Temperature Compensated Crystal Oscillator (TCXO) and external rubidium oscillator.
Nanosecond-level timing solutions from Global Navigation Satellite Systems (GNSS), such as the Global Positioning System (GPS), are integrated into many personal and industrial systems, including transportation, communications systems, electrical power grids, and financial institutions. However, due the orbital altitude of the satellites, the received signal power of the end user is critically low, resulting in vulnerable timing solutions. The Low-Earth Orbit (LEO) Iridium constellation orbits significantly closer to Earth’s surface, ensuring higher received signal strength. While the system was originally intended for communications, the satellites have been updated to broadcast the STL message, which can be used for navigation applications.
The results of these experiments indicate that the Iridium STL signal is capable of providing GNSS-independent, nanosecond-level timing accuracy for stationary receivers. Throughout the 120 hours of data collected, the receiver timing accuracy was maintained to within a mean timing error of less than 205 nanoseconds. The timing state estimation experiment demonstrates a substantial improvement in timing performance when the receiver position is provided to the estimator, resulting in standard deviations of less than 1 nanosecond per second. The 1-PPS time interval experiment shows the off-the-shelf capabilities of the STL receiver to be accurate to within 110 nanoseconds of deviation and approximately 500 nanoseconds of error at all times. The second experiment also indicates the maximum timing error and deviation can be reduced when a high-fidelity, rubidium oscillator is integrated into the receiver hardware.},
	language = {en},
	urldate = {2024-06-25},
	author = {Smith, Austin},
	month = dec,
	year = {2023},
	note = {Accepted: 2023-12-06T20:16:57Z},
}

This thesis assesses the accuracy, stability, and convergence rates of receiver timing solutions with the Iridium Satellite Time and Location (STL) signal through two studies. In the first experiment, an Extended Kalman Filter (EKF) and a Weighted Least Squares (WLS) solution are used to estimate the clock states of a static receiver at an antenna location which is known and unknown, respectively. In the second experiment, a 1-PPS (Pulse-Per-Second) time interval study is conducted with two, commercially-available Jackson Labs Technologies STL-2600 receivers, which are both provided a precise position. Both tests are conducted using an on-board Temperature Compensated Crystal Oscillator (TCXO) and external rubidium oscillator. Nanosecond-level timing solutions from Global Navigation Satellite Systems (GNSS), such as the Global Positioning System (GPS), are integrated into many personal and industrial systems, including transportation, communications systems, electrical power grids, and financial institutions. However, due the orbital altitude of the satellites, the received signal power of the end user is critically low, resulting in vulnerable timing solutions. The Low-Earth Orbit (LEO) Iridium constellation orbits significantly closer to Earth’s surface, ensuring higher received signal strength. While the system was originally intended for communications, the satellites have been updated to broadcast the STL message, which can be used for navigation applications. The results of these experiments indicate that the Iridium STL signal is capable of providing GNSS-independent, nanosecond-level timing accuracy for stationary receivers. Throughout the 120 hours of data collected, the receiver timing accuracy was maintained to within a mean timing error of less than 205 nanoseconds. The timing state estimation experiment demonstrates a substantial improvement in timing performance when the receiver position is provided to the estimator, resulting in standard deviations of less than 1 nanosecond per second. The 1-PPS time interval experiment shows the off-the-shelf capabilities of the STL receiver to be accurate to within 110 nanoseconds of deviation and approximately 500 nanoseconds of error at all times. The second experiment also indicates the maximum timing error and deviation can be reduced when a high-fidelity, rubidium oscillator is integrated into the receiver hardware.

@unpublished{morgan_gps_2023,
	title = {A {GPS} {L1} and {Cellular} {4G} {LTE} {Vector} {Tracking} {Software}-{Defined} {Receiver}},
	url = {https://etd.auburn.edu//handle/10415/9005},
	abstract = {In this thesis, a traditional GPS L1 vector tracking receiver is augmented with cellular 4G LTE channels. The hybrid receiver can acquire and track GPS L1 and LTE signals simultaneously in an extended Kalman filter-based vector tracking loop. The receiver uses either the secondary synchronization signal or the cell-specific reference signal to track the LTE signals. First, the open-loop pseudorange and pseudorange rate errors are provided as a function of the carrier-to-noise ratio. A method to calculate the carrier-to-noise ratio of the LTE signal using correlator outputs is also provided. The code phase and carrier frequency tracking accuracy of the receiver is derived in theory using the Discrete Algebraic Riccati Equation (DARE) and validated by Monte Carlo simulations. The effects of errors, such as eNodeB localization error and multipath, are evaluated in Monte Carlo simulations as well. The robustness of the combined vector tracking loop to GPS outages is also evaluated in Monte Carlo simulations. Finally, the positioning accuracy of a prototype of the hybrid receiver is shown experimentally.},
	language = {en},
	urldate = {2024-06-25},
	author = {Morgan, Samuel},
	month = nov,
	year = {2023},
	note = {Accepted: 2023-11-17T16:05:52Z},
}

In this thesis, a traditional GPS L1 vector tracking receiver is augmented with cellular 4G LTE channels. The hybrid receiver can acquire and track GPS L1 and LTE signals simultaneously in an extended Kalman filter-based vector tracking loop. The receiver uses either the secondary synchronization signal or the cell-specific reference signal to track the LTE signals. First, the open-loop pseudorange and pseudorange rate errors are provided as a function of the carrier-to-noise ratio. A method to calculate the carrier-to-noise ratio of the LTE signal using correlator outputs is also provided. The code phase and carrier frequency tracking accuracy of the receiver is derived in theory using the Discrete Algebraic Riccati Equation (DARE) and validated by Monte Carlo simulations. The effects of errors, such as eNodeB localization error and multipath, are evaluated in Monte Carlo simulations as well. The robustness of the combined vector tracking loop to GPS outages is also evaluated in Monte Carlo simulations. Finally, the positioning accuracy of a prototype of the hybrid receiver is shown experimentally.

@unpublished{moomaw_decentralized_2023,
	title = {Decentralized {Collaborative} {Navigation} in {Limited} {Observability} {Environments} with {Low} {Earth} {Orbit} {Satellite} {Signals} of {Opportunity} between {Aerial} and {Ground} {Vehicles}},
	url = {https://etd.auburn.edu//handle/10415/8839},
	abstract = {A decentralized collaborative navigation algorithm known as inverse covariance intersection (ICI) is studied in the context of a group of vehicles navigating using opportunistic Doppler measurements. Signals of opportunity (SOOPs) have been extensively studied for applications requiring reliable position, velocity, and timing (PVT) information in conditions with potentially degraded GNSS performance. Doppler measurements derived from SOOPs can be used for positioning when GNSS signals are unavailable, but the resulting position estimate accuracy from Doppler-only techniques is unacceptably poor for many use cases. Collaborative techniques can leverage high-quality peer-to-peer range measurements to constrain PVT estimate error growth for each vehicle in a collaborating group.

A navigator employing a tightly-coupled Doppler-inertial extended Kalman filter (EKF) is developed. Its performance is analyzed using Monte Carlo techniques and simulated Doppler measurements from a collection of satellites in low earth orbit (LEO). Peer-to-peer range measurements are integrated using techniques including the well-known covariance intersection (CI), ICI, and a centralized EKF. The performance gains of each method are presented as compared to non-cooperating vehicles. Additionally, the two decentralized navigators are each compared to the centralized navigator, which represents a reasonable best case. The proposed ICI-based navigator is shown using a Monte Carlo test to achieve 62\% of the position error reduction of an ideal centralized navigator in the average case, compared to 28\% for the well-studied CI-based technique. The proposed ICI navigator is tested with experimentally-collected ranges from ultrawideband transceivers and is shown remain functional in the presence of faulty range measurements.},
	language = {en},
	urldate = {2024-06-25},
	author = {Moomaw, Christian},
	month = jul,
	year = {2023},
	note = {Accepted: 2023-07-28T13:24:55Z},
}

A decentralized collaborative navigation algorithm known as inverse covariance intersection (ICI) is studied in the context of a group of vehicles navigating using opportunistic Doppler measurements. Signals of opportunity (SOOPs) have been extensively studied for applications requiring reliable position, velocity, and timing (PVT) information in conditions with potentially degraded GNSS performance. Doppler measurements derived from SOOPs can be used for positioning when GNSS signals are unavailable, but the resulting position estimate accuracy from Doppler-only techniques is unacceptably poor for many use cases. Collaborative techniques can leverage high-quality peer-to-peer range measurements to constrain PVT estimate error growth for each vehicle in a collaborating group. A navigator employing a tightly-coupled Doppler-inertial extended Kalman filter (EKF) is developed. Its performance is analyzed using Monte Carlo techniques and simulated Doppler measurements from a collection of satellites in low earth orbit (LEO). Peer-to-peer range measurements are integrated using techniques including the well-known covariance intersection (CI), ICI, and a centralized EKF. The performance gains of each method are presented as compared to non-cooperating vehicles. Additionally, the two decentralized navigators are each compared to the centralized navigator, which represents a reasonable best case. The proposed ICI-based navigator is shown using a Monte Carlo test to achieve 62% of the position error reduction of an ideal centralized navigator in the average case, compared to 28% for the well-studied CI-based technique. The proposed ICI navigator is tested with experimentally-collected ranges from ultrawideband transceivers and is shown remain functional in the presence of faulty range measurements.

@unpublished{mifflin_online_2023,
	title = {Online {Autonomous} {Extrinsic} {Calibration} of an {Inertial} {Measurement} {Unit} using {Gaussian} {Radial} {Basis} {Function} {Neural} {Networks}},
	url = {https://etd.auburn.edu//handle/10415/8945},
	abstract = {This thesis presents a fully online and autonomous method to extrinsically calibrate an inertial measurement unit (IMU) to the body frame of a vehicle. Extrinsic sensor calibration is an important step in obtaining valid information in the vehicle frame, without which an autonomous vehicle cannot function properly. Traditionally, a manual calibration routine must be performed by a set of trained experts to a high degree of precision before the vehicle can be safely operated. This procedure costs time and money and limits the design of the sensor suite. An online and autonomous calibration method would eliminate this constraint, saving time, and allowing for the dynamic reconfiguration of the sensor suite. The autonomous IMU-to-Vehicle calibration procedure presented in this thesis is conducted in a two-stage process. First, a gaussian radial basis function neural network is used to emulate the output of a virtual IMU in the vehicle frame. Then, a maximum likelihood search algorithm estimates the extrinsic calibration parameters by performing an IMU-to-IMU calibration between the IMU on the body of the vehicle, and the emulated IMU. The IMU emulation method obtains high-fidelity acceleration estimates on both simulated and experimental data sets. The maximum likelihood search method obtains sensor position estimates within 2 mm of the true sensor location in each direction and within 0.2 degrees of the true sensor orientation for a battery of tests in simulation. In experimental tests, this method estimated the true lateral and longitudinal sensor positions to within 3 cm, and the true sensor orientation to within 0.25 \${\textbackslash}circ\$ in each direction.},
	language = {en},
	urldate = {2024-06-25},
	author = {Mifflin, Gregory},
	month = aug,
	year = {2023},
	note = {Accepted: 2023-08-07T18:59:33Z},
}

This thesis presents a fully online and autonomous method to extrinsically calibrate an inertial measurement unit (IMU) to the body frame of a vehicle. Extrinsic sensor calibration is an important step in obtaining valid information in the vehicle frame, without which an autonomous vehicle cannot function properly. Traditionally, a manual calibration routine must be performed by a set of trained experts to a high degree of precision before the vehicle can be safely operated. This procedure costs time and money and limits the design of the sensor suite. An online and autonomous calibration method would eliminate this constraint, saving time, and allowing for the dynamic reconfiguration of the sensor suite. The autonomous IMU-to-Vehicle calibration procedure presented in this thesis is conducted in a two-stage process. First, a gaussian radial basis function neural network is used to emulate the output of a virtual IMU in the vehicle frame. Then, a maximum likelihood search algorithm estimates the extrinsic calibration parameters by performing an IMU-to-IMU calibration between the IMU on the body of the vehicle, and the emulated IMU. The IMU emulation method obtains high-fidelity acceleration estimates on both simulated and experimental data sets. The maximum likelihood search method obtains sensor position estimates within 2 mm of the true sensor location in each direction and within 0.2 degrees of the true sensor orientation for a battery of tests in simulation. In experimental tests, this method estimated the true lateral and longitudinal sensor positions to within 3 cm, and the true sensor orientation to within 0.25 ${\}circ$ in each direction.

@unpublished{mcdougal_software_2023,
	title = {A {Software} {Signal} {Simulation} of {Low} {Earth} {Orbit} {Satellites} for {Investigative} {Analysis}},
	url = {https://etd.auburn.edu//handle/10415/8697},
	abstract = {Simulation tools are an important part of the engineering design process by allowing changes in algorithms and processes before  implementation. Current global navigation satellite systems (GNSSs) are mainly located in medium Earth orbit (MEO) and have been used for many decades. GNSSs are used for positioning applications all across the globe from civilian to military applications. These satellite systems work well in most applications, however they are susceptible to interferences due to low signal power. Low Earth orbit (LEO) satellites have gained interest as a possible alternative source of position, navigation, and timing (PNT). This is because LEO satellites have higher received signal power compared to standard GNSSs. One issue with LEO satellites is that the signal was not initially designed for navigation and most of the messages are unknown. 

This thesis describes the design of a software signal simulation tool for LEO satellites for investigative purposes. The tool is modular to allow for simulation blocks to be changed quickly and efficiently. This design also allows for new pieces to be written and integrated easily. The MATLAB simulation is capable of generating complex in-phase and quadrature signals for time division multiple access signals for current and hypothetical LEO constellations. A customized navigation message was developed to account for multiple user selected formats. The signals generated by this simulation tool can be passed through a software receiver and through hardware by means of a universal software radio peripheral. By generating simulated signals, receivers can be designed and tested. To test the generated signals, a specialized receiver was designed. The output navigation data is used to produce position estimates for static receiver positions using batched Doppler and pseudorange based least squares algorithms. The simulation tool is shown to be flexible in order to examine varying test plans.},
	language = {en},
	urldate = {2024-06-25},
	author = {McDougal, Samuel},
	month = may,
	year = {2023},
	note = {Accepted: 2023-05-02T13:30:30Z},
}

Simulation tools are an important part of the engineering design process by allowing changes in algorithms and processes before implementation. Current global navigation satellite systems (GNSSs) are mainly located in medium Earth orbit (MEO) and have been used for many decades. GNSSs are used for positioning applications all across the globe from civilian to military applications. These satellite systems work well in most applications, however they are susceptible to interferences due to low signal power. Low Earth orbit (LEO) satellites have gained interest as a possible alternative source of position, navigation, and timing (PNT). This is because LEO satellites have higher received signal power compared to standard GNSSs. One issue with LEO satellites is that the signal was not initially designed for navigation and most of the messages are unknown. This thesis describes the design of a software signal simulation tool for LEO satellites for investigative purposes. The tool is modular to allow for simulation blocks to be changed quickly and efficiently. This design also allows for new pieces to be written and integrated easily. The MATLAB simulation is capable of generating complex in-phase and quadrature signals for time division multiple access signals for current and hypothetical LEO constellations. A customized navigation message was developed to account for multiple user selected formats. The signals generated by this simulation tool can be passed through a software receiver and through hardware by means of a universal software radio peripheral. By generating simulated signals, receivers can be designed and tested. To test the generated signals, a specialized receiver was designed. The output navigation data is used to produce position estimates for static receiver positions using batched Doppler and pseudorange based least squares algorithms. The simulation tool is shown to be flexible in order to examine varying test plans.

@unpublished{kennedy_adaptive_2023,
	title = {Adaptive {Steering} {Actuator} {Delay} {Compensation} for a {Vehicle} {Lateral} {Control} {System}},
	url = {https://etd.auburn.edu//handle/10415/8690},
	abstract = {This thesis presents an adaptive control algorithm for steering actuator delay compensation in a ground vehicle lateral control system. Unknown and time-varying actuator delay values are considered. Many active safety systems and all autonomous vehicles rely on a lateral control system in order to follow a desired path. Lateral control systems designed without considering actuator delay may not achieve desired path following performance or may exhibit an undesirable system response such as steering oscillation, resulting in an uncomfortable ride or even instability or collisions. The delay compensating controller presented in this thesis is implemented at a low level within the lateral control system. It attempts to mitigate the effects of the time delay without using a vehicle model or altering the high level path following controller. The estimation algorithm used in this thesis utilizes knowledge of the control input and measured steer angle to estimate both the communication delay and the actuator dynamics present in the control system. This allows the compensating controller to adapt to changing or unknown actuator delay. The performance of the inner-loop compensation algorithm is evaluated with multiple path following controllers. The controller is then tested in a lane-keeping simulation, and finally applied to a real-world path following experiment. The proposed compensation algorithm is shown in both simulation and real-time tests to improve steering response and overall path following performance.},
	language = {en},
	urldate = {2024-06-25},
	author = {Kennedy, William},
	month = may,
	year = {2023},
	note = {Accepted: 2023-05-01T18:07:51Z},
}

This thesis presents an adaptive control algorithm for steering actuator delay compensation in a ground vehicle lateral control system. Unknown and time-varying actuator delay values are considered. Many active safety systems and all autonomous vehicles rely on a lateral control system in order to follow a desired path. Lateral control systems designed without considering actuator delay may not achieve desired path following performance or may exhibit an undesirable system response such as steering oscillation, resulting in an uncomfortable ride or even instability or collisions. The delay compensating controller presented in this thesis is implemented at a low level within the lateral control system. It attempts to mitigate the effects of the time delay without using a vehicle model or altering the high level path following controller. The estimation algorithm used in this thesis utilizes knowledge of the control input and measured steer angle to estimate both the communication delay and the actuator dynamics present in the control system. This allows the compensating controller to adapt to changing or unknown actuator delay. The performance of the inner-loop compensation algorithm is evaluated with multiple path following controllers. The controller is then tested in a lane-keeping simulation, and finally applied to a real-world path following experiment. The proposed compensation algorithm is shown in both simulation and real-time tests to improve steering response and overall path following performance.

@unpublished{keefer_real-time_2023,
	title = {Real-{Time} {Graph}-{Based} {Path} {Planning} for {Autonomous} {Racecars}},
	url = {https://etd.auburn.edu//handle/10415/8803},
	abstract = {This thesis presents a computationally efficient graph-based motion planner designed for
high speed autonomous racing. The emergence of autonomous racing competitions, such as the
Indy Autonomous Challenge (IAC), have sought to test the limits of autonomous vehicle tech-
nology to accelerate development within the domain. A fast, safe, and reliable motion planning
algorithm is developed for an autonomous vehicle operating under high-speed conditions such
as the ones in the IAC. A variety of planning methods are investigated for this purpose, such
as graph-based planning and sampling-based planning, among others. A graph-based method
using the A* search algorithm is selected due to its computational efficiency, reliability, and
predictability in structured environments. The proposed planner is augmented with techniques
for integrating vehicular constraints with path smoothing and edge generation.


Two versions of the proposed path planner are presented. The version used for the 2021
and 2022 IAC competitions on oval tracks is developed and test results from simulation and
running the planner in real time competition are presented. Additionally, improvements to the
planner are implemented to enhance the dynamic feasibility of the planned path and allow for
use on road courses. The improved planner is tested on an autonomous consumer sedan as well
as in simulation. Both iterations of the proposed algorithm are shown to produce dynamically
feasible maneuvers in the presence of a priori unknown obstacles while maintaining faster than
real-time performance.},
	language = {en},
	urldate = {2024-06-25},
	author = {Keefer, Sarah Elizabeth},
	month = jul,
	year = {2023},
	note = {Accepted: 2023-07-27T15:19:19Z},
}

This thesis presents a computationally efficient graph-based motion planner designed for high speed autonomous racing. The emergence of autonomous racing competitions, such as the Indy Autonomous Challenge (IAC), have sought to test the limits of autonomous vehicle tech- nology to accelerate development within the domain. A fast, safe, and reliable motion planning algorithm is developed for an autonomous vehicle operating under high-speed conditions such as the ones in the IAC. A variety of planning methods are investigated for this purpose, such as graph-based planning and sampling-based planning, among others. A graph-based method using the A* search algorithm is selected due to its computational efficiency, reliability, and predictability in structured environments. The proposed planner is augmented with techniques for integrating vehicular constraints with path smoothing and edge generation. Two versions of the proposed path planner are presented. The version used for the 2021 and 2022 IAC competitions on oval tracks is developed and test results from simulation and running the planner in real time competition are presented. Additionally, improvements to the planner are implemented to enhance the dynamic feasibility of the planned path and allow for use on road courses. The improved planner is tested on an autonomous consumer sedan as well as in simulation. Both iterations of the proposed algorithm are shown to produce dynamically feasible maneuvers in the presence of a priori unknown obstacles while maintaining faster than real-time performance.

@unpublished{jones_loosely_2023,
	title = {A {Loosely} {Coupled} {GNSS}/{PDR} {Integration} {Approach} for {Pedestrian} {Navigation}},
	url = {https://etd.auburn.edu//handle/10415/8840},
	abstract = {Pedestrian navigation systems embody small, lightweight hardware, techniques, and biomechanical information to provide positioning information in an architecture that substitutes, or supplements, traditional systems such as GNSS. Two unique challenges of pedestrian navigation systems are the hardware size and weight constraints to keep the user comfortable, while the other challenge is the ability to provide accuracy and stability of the navigation solution in certain environments. Existing systems rely on the availability of small, lightweight, GNSS and inertial hardware for position, velocity, and attitude information in challenging environments. This thesis presents methods of integrating GNSS with a torso-mounted IMU to estimate three physical parameters of the user and the system hardware as a means of providing longer stability of the position, velocity, and attitude estimates when GNSS is no longer available. The presented methods will include showcasing a method of estimating the user's step length with existing models, as well as a new model; a method of hardware misalignment compensation for heading estimation; and an approach to detecting erroneous magnetometer measurements to reduce errors in the user's heading. GNSS is utilized in conjunction with the IMU to provide discrete step length pseudo-measurements for the user's step length estimation; GNSS course measurements will be used to estimate heading misalignment between the user and the IMU; and, finally, a threshold metric of the magnetometer measurements is used to compensate for errors in heading that would occur from perturbed magnetic field measurements. Performance analyses of each method is shown using real data with simulated GNSS outages. The methods are implemented using IMU data from a Vectornav 9-DoF VN-100 and a Ublox EVK-7 GNSS receiver for some data sets, and a Ublox ZED-F9P GNSS receiver for other data sets. Conclusions drawn from results of each method implementation are discussed and summarized.},
	language = {en},
	urldate = {2024-06-25},
	author = {Jones, Connor},
	month = jul,
	year = {2023},
	note = {Accepted: 2023-07-28T13:31:08Z},
}

Pedestrian navigation systems embody small, lightweight hardware, techniques, and biomechanical information to provide positioning information in an architecture that substitutes, or supplements, traditional systems such as GNSS. Two unique challenges of pedestrian navigation systems are the hardware size and weight constraints to keep the user comfortable, while the other challenge is the ability to provide accuracy and stability of the navigation solution in certain environments. Existing systems rely on the availability of small, lightweight, GNSS and inertial hardware for position, velocity, and attitude information in challenging environments. This thesis presents methods of integrating GNSS with a torso-mounted IMU to estimate three physical parameters of the user and the system hardware as a means of providing longer stability of the position, velocity, and attitude estimates when GNSS is no longer available. The presented methods will include showcasing a method of estimating the user's step length with existing models, as well as a new model; a method of hardware misalignment compensation for heading estimation; and an approach to detecting erroneous magnetometer measurements to reduce errors in the user's heading. GNSS is utilized in conjunction with the IMU to provide discrete step length pseudo-measurements for the user's step length estimation; GNSS course measurements will be used to estimate heading misalignment between the user and the IMU; and, finally, a threshold metric of the magnetometer measurements is used to compensate for errors in heading that would occur from perturbed magnetic field measurements. Performance analyses of each method is shown using real data with simulated GNSS outages. The methods are implemented using IMU data from a Vectornav 9-DoF VN-100 and a Ublox EVK-7 GNSS receiver for some data sets, and a Ublox ZED-F9P GNSS receiver for other data sets. Conclusions drawn from results of each method implementation are discussed and summarized.

@unpublished{flegel_relative_2023,
	title = {Relative {Position} {Vector} {Generation} with {Computer} {Vision} for {Vehicle} {Platooning} {Applications}},
	url = {https://etd.auburn.edu//handle/10415/8927},
	abstract = {Many significant advances have been made in autonomous vehicle technology over the recent decades. This includes platooning of heavy trucks. As such, many institutions have created their own version of the basic platooning platform. This includes the California
PATH program [1], Japan’s ”Energy ITS” project [2], and Auburn University’s CACC Platform [3]. One thing these platforms have in common is a strong dependence on GPS based localization solutions. Issues arise when the platoon navigates into challenging environments,
including rural areas with foliage which might block receptions, or more populated areas which might present urban canyon effects. Recent research focus has shifted to handling these situations through the use of alternative sensors, including cameras. The perception method proposed in this thesis utilizes the You Only Look Once (YOLO) real-time object detection algorithm in order to bound the lead vehicle using both RGB and IR cameras. Two different YOLO variants were evaluated: YOLOv3 and TinyYOLOv3. Monocular range is determined using both the classical pinhole model and virtual horizon ranging model. A bearing model is introduced which uses the range to determine bearing to the lead vehicle. Various combinations of cameras, YOLO models, and ranging models are then tested on heavy duty truck data collected on roads near Auburn University’s NCAT facility. The results shown in this thesis reveal that there is a slight range accuracy advantage to YOLOv3 on both the pinhole camera model and the Virtual horizon model. TinyYolo was shown to have a faster processing speed which would be ideal in highly dynamic situations. Using the results from the on road truck analysis, a real-time implementation was developed using two consumer sedans. During analysis it was discovered that YOLO had momentary lapses in which it would not detect the lead vehicle, and would therefore not be able to provide range and bearing measurements. To address this, a sub-tracking algorithm was developed. The algorithm was developed around established tracking algorithms, and analysis was performed to determine which tracking algorithm was best suited for dynamic vehicle tracking. Additionally, a slight variation of the method was developed which utilized a stereoscopic camera. The sub-tracking algorithm and stereoscopic vehicle detection algorithm were evaluated in several real-time platooning scenarios, in which the following vehicle operated autonomously using lateral control.},
	language = {en},
	urldate = {2024-06-25},
	author = {Flegel, Tyler},
	month = aug,
	year = {2023},
	note = {Accepted: 2023-08-04T17:59:10Z},
}

Many significant advances have been made in autonomous vehicle technology over the recent decades. This includes platooning of heavy trucks. As such, many institutions have created their own version of the basic platooning platform. This includes the California PATH program [1], Japan’s ”Energy ITS” project [2], and Auburn University’s CACC Platform [3]. One thing these platforms have in common is a strong dependence on GPS based localization solutions. Issues arise when the platoon navigates into challenging environments, including rural areas with foliage which might block receptions, or more populated areas which might present urban canyon effects. Recent research focus has shifted to handling these situations through the use of alternative sensors, including cameras. The perception method proposed in this thesis utilizes the You Only Look Once (YOLO) real-time object detection algorithm in order to bound the lead vehicle using both RGB and IR cameras. Two different YOLO variants were evaluated: YOLOv3 and TinyYOLOv3. Monocular range is determined using both the classical pinhole model and virtual horizon ranging model. A bearing model is introduced which uses the range to determine bearing to the lead vehicle. Various combinations of cameras, YOLO models, and ranging models are then tested on heavy duty truck data collected on roads near Auburn University’s NCAT facility. The results shown in this thesis reveal that there is a slight range accuracy advantage to YOLOv3 on both the pinhole camera model and the Virtual horizon model. TinyYolo was shown to have a faster processing speed which would be ideal in highly dynamic situations. Using the results from the on road truck analysis, a real-time implementation was developed using two consumer sedans. During analysis it was discovered that YOLO had momentary lapses in which it would not detect the lead vehicle, and would therefore not be able to provide range and bearing measurements. To address this, a sub-tracking algorithm was developed. The algorithm was developed around established tracking algorithms, and analysis was performed to determine which tracking algorithm was best suited for dynamic vehicle tracking. Additionally, a slight variation of the method was developed which utilized a stereoscopic camera. The sub-tracking algorithm and stereoscopic vehicle detection algorithm were evaluated in several real-time platooning scenarios, in which the following vehicle operated autonomously using lateral control.

@unpublished{steadman_teleoperated_2023,
	title = {Teleoperated {Ground} {Vehicle} {Rollover} {Prediction} via the {ZMP} {Index} using the {Forward} {Euler} {Method}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/8882},
	abstract = {AUETD thesis upload not permitted without sponsor approval.},
	language = {en},
	urldate = {2024-06-25},
	author = {Steadman, Kathleen},
	month = aug,
	year = {2023},
	note = {Accepted: 2023-08-02T16:36:04Z},
}

AUETD thesis upload not permitted without sponsor approval.

@unpublished{stubbs_improving_2023,
	title = {Improving {Semi}-autonomous {Unmanned} {Ground} {Vehicle} {Operator} {Performance} via {Haptics}},
	copyright = {EMBARGO\_GLOBAL},
	url = {https://etd.auburn.edu//handle/10415/8645},
	abstract = {This thesis has not been approved for public release.},
	language = {en},
	urldate = {2024-06-25},
	author = {Stubbs, Chandler},
	month = apr,
	year = {2023},
	note = {Accepted: 2023-04-26T18:42:20Z},
}

This thesis has not been approved for public release.

@inproceedings{bentley_comparing_2023,
	address = {Warrendale, PA},
	title = {Comparing the {Performance} of {Different} {Heavy} {Duty} {Platooning} {Control} {Strategies}},
	url = {https://www.sae.org/publications/technical-papers/content/2023-01-0895/},
	abstract = {Platooning is a promising technology which can mitigate greenhouse gas impacts and reduce transportation energy consumption. Platooning is a coordinated driving strategy where trucks align themselves in order to realize aerodynamic benefits to reduce required motive force. The aerodynamic benefit is},
	language = {English},
	urldate = {2024-06-20},
	publisher = {SAE Technical Paper},
	author = {Bentley, John William and Snitzer, Philip and Stegner, Evan and Bevly, David M. and Hoffman, Mark},
	month = apr,
	year = {2023},
	doi = {10.4271/2023-01-0895},
}

Platooning is a promising technology which can mitigate greenhouse gas impacts and reduce transportation energy consumption. Platooning is a coordinated driving strategy where trucks align themselves in order to realize aerodynamic benefits to reduce required motive force. The aerodynamic benefit is

@inproceedings{kennedy_adaptive_2023,
	address = {Warrendale, PA},
	title = {Adaptive {Actuator} {Delay} {Compensation} for a {Vehicle} {Lateral} {Control} {System}},
	url = {https://www.sae.org/publications/technical-papers/content/2023-01-0677/},
	abstract = {Steering actuator lag is detrimental to the performance of lateral control systems and often leads to oscillation, reduced stability margins, and in some cases, instability. If the actuator lag is significant, compensation is required to maintain stability and meet performance specifications. Many r},
	language = {English},
	urldate = {2024-06-20},
	publisher = {SAE Technical Paper},
	author = {Kennedy, William Thomas and Bevly, David M.},
	month = apr,
	year = {2023},
	doi = {10.4271/2023-01-0677},
}

Steering actuator lag is detrimental to the performance of lateral control systems and often leads to oscillation, reduced stability margins, and in some cases, instability. If the actuator lag is significant, compensation is required to maintain stability and meet performance specifications. Many r

@inproceedings{snitzer_new_2023,
	address = {Warrendale, PA},
	title = {New {Controller} {Evaluation} {Techniques} for {Autonomously} {Driven} {Heavy}-{Duty} {Convoys}},
	url = {https://www.sae.org/publications/technical-papers/content/2023-01-0688/},
	abstract = {Platooning vehicles present novel pathways to saving fuel during transportation. With the rise of autonomous solutions, platooning becomes an increasingly apparent sector requiring the application of this new technology. Platooning vehicles travel together intending to reduce aerodynamic resistance},
	language = {English},
	urldate = {2024-06-20},
	publisher = {SAE Technical Paper},
	author = {Snitzer, Philip and Stegner, Evan and Bentley, John and Bevly, David M. and Hoffman, Mark},
	month = apr,
	year = {2023},
	doi = {10.4271/2023-01-0688},
}

Platooning vehicles present novel pathways to saving fuel during transportation. With the rise of autonomous solutions, platooning becomes an increasingly apparent sector requiring the application of this new technology. Platooning vehicles travel together intending to reduce aerodynamic resistance

@inproceedings{stegner_quantifying_2023,
	address = {Warrendale, PA},
	title = {Quantifying the {Energy} {Impact} of {Autonomous} {Platooning}-{Imposed} {Longitudinal} {Dynamics}},
	url = {https://www.sae.org/publications/technical-papers/content/2023-01-0896/},
	abstract = {Platooning has produced significant energy savings for vehicles in a controlled environment. However, the impact of real-world disturbances, such as grade and interactions with passenger vehicles, has not been sufficiently characterized. Follower vehicles in a platoon operate with both different aer},
	language = {English},
	urldate = {2024-06-20},
	publisher = {SAE Technical Paper},
	author = {Stegner, Evan and Snitzer, Philip and Bentley, John and Bevly, David M. and Hoffman, Mark},
	month = apr,
	year = {2023},
	doi = {10.4271/2023-01-0896},
}

Platooning has produced significant energy savings for vehicles in a controlled environment. However, the impact of real-world disturbances, such as grade and interactions with passenger vehicles, has not been sufficiently characterized. Follower vehicles in a platoon operate with both different aer

@inproceedings{ward_design_2023,
	title = {Design and {Implementation} of an {SAE} {Level}-2 {Lane} {Keeping} {System} for {Class} 8 {Trucks} {Using} {Nonlinear} {Model} {Predictive} {Control}},
	url = {https://ieeexplore.ieee.org/abstract/document/10253308},
	doi = {10.1109/CCTA54093.2023.10253308},
	abstract = {This paper focuses on the design and evaluation of a lateral Nonlinear Model Predictive Control (NMPC) path following algorithm for Class 8 vehicles. While NMPC allows for the inclusion of constraints such as obstacle avoidance or rollover prevention, this work is primarily focused on testing the path following capabilities of the NMPC controller without the consideration of constraints. Although many lateral controllers for tractor-trailer systems use either fully linear or fully nonlinear Equations of Motion (EOMs), this paper presents a hybrid model. This hybrid model uses a linear model to describe the dynamics of the tractor-trailer while using nonlinear equations to describe the global position of the system. This model is then implemented in a NMPC architecture. The controller is first designed and tested in MATLAB to yield a controller that can follow a lane change maneuver. This controller is then implemented in a real-time format using ROS and C++. The objective of the real-time controller was to replicate the path of a Kia Optima which was driving in front of the test vehicle. To accomplish this, an estimator was developed to calculate the relative path between the vehicles with enough accuracy to stay within the standard road lane. This estimation algorithm was able to produce lateral position errors with a standard deviation of 1.96 cm. Finally, the lateral controller was shown to track the generated reference path with a mean error of 1.47 cm and a RMS error of under 27 cm.},
	urldate = {2024-06-20},
	booktitle = {2023 {IEEE} {Conference} on {Control} {Technology} and {Applications} ({CCTA})},
	author = {Ward, Jacob W. and Pierce, J. Daniel and Brown, Lowell and Bevly, David M.},
	month = aug,
	year = {2023},
	note = {ISSN: 2768-0770},
	keywords = {Collision avoidance, GNSS, Lateral Control, Mathematical models, NMPC, Nonlinear dynamical systems, Nonlinear equations, Path Duplication, Real-time systems, Rollover, Transient analysis},
	pages = {841--846},
}

This paper focuses on the design and evaluation of a lateral Nonlinear Model Predictive Control (NMPC) path following algorithm for Class 8 vehicles. While NMPC allows for the inclusion of constraints such as obstacle avoidance or rollover prevention, this work is primarily focused on testing the path following capabilities of the NMPC controller without the consideration of constraints. Although many lateral controllers for tractor-trailer systems use either fully linear or fully nonlinear Equations of Motion (EOMs), this paper presents a hybrid model. This hybrid model uses a linear model to describe the dynamics of the tractor-trailer while using nonlinear equations to describe the global position of the system. This model is then implemented in a NMPC architecture. The controller is first designed and tested in MATLAB to yield a controller that can follow a lane change maneuver. This controller is then implemented in a real-time format using ROS and C++. The objective of the real-time controller was to replicate the path of a Kia Optima which was driving in front of the test vehicle. To accomplish this, an estimator was developed to calculate the relative path between the vehicles with enough accuracy to stay within the standard road lane. This estimation algorithm was able to produce lateral position errors with a standard deviation of 1.96 cm. Finally, the lateral controller was shown to track the generated reference path with a mean error of 1.47 cm and a RMS error of under 27 cm.

@inproceedings{miller_snap_2023,
	title = {{SNAP}: {A} {Xona} {Space} {Systems} and {GPS} {Software}-{Defined} {Receiver}},
	shorttitle = {{SNAP}},
	url = {https://ieeexplore.ieee.org/abstract/document/10139956},
	doi = {10.1109/PLANS53410.2023.10139956},
	abstract = {This paper proposes the Satellite Navigation Applied Processor (SNAP), a Software Defined Receiver (SDR) for the Xona Space Systems Pulsar constellation and legacy Global Navigation Satellite Systems (GNSS). The novelty of this paper is found in the creation of an SDR that serves to explore the capabilities of a new Low Earth Orbit (LEO) satellite navigation constellation. The modularity of SNAP allows both industry professionals and students to investigate their own Pulsar and legacy GNSS signal processing techniques.},
	urldate = {2024-06-20},
	booktitle = {2023 {IEEE}/{ION} {Position}, {Location} and {Navigation} {Symposium} ({PLANS})},
	author = {Miller, Noah S. and Koza, J. Tanner and Morgan, Samuel C. and Martin, Scott M. and Neish, Andrew and Grayson, Robert and Reid, Tyler},
	month = apr,
	year = {2023},
	note = {ISSN: 2153-3598},
	keywords = {Global navigation satellite system, Industries, LEO Satellites, Low earth orbit satellites, Receivers, Satellites, Signal Processing, Signal processing, Software Defined Receivers, Space vehicles},
	pages = {897--904},
}

This paper proposes the Satellite Navigation Applied Processor (SNAP), a Software Defined Receiver (SDR) for the Xona Space Systems Pulsar constellation and legacy Global Navigation Satellite Systems (GNSS). The novelty of this paper is found in the creation of an SDR that serves to explore the capabilities of a new Low Earth Orbit (LEO) satellite navigation constellation. The modularity of SNAP allows both industry professionals and students to investigate their own Pulsar and legacy GNSS signal processing techniques.

@inproceedings{abbas_numerical_2023,
	address = {Stavropol, Russia},
	title = {Numerical solutions for {Taylor} and {Runge}-{Kutta} methods with ordinary differential equations-comparing to analytical solutions},
	url = {http://aip.scitation.org/doi/abs/10.1063/5.0178825},
	doi = {10.1063/5.0178825},
	urldate = {2024-06-20},
	author = {Abbas, Ali Fahem and Ali, Ali Jalal},
	year = {2023},
	pages = {030003},
}

@inproceedings{boler_essential_2023,
	title = {Essential {PoseSLAM}: {An} {Efficient} {Landmark}-{Free} {Approach} to {Visual}-{Inertial} {Navigation}},
	shorttitle = {Essential {PoseSLAM}},
	url = {https://ieeexplore.ieee.org/document/10140080/;jsessionid=340C8E9C04310C1313356D39692E9E64},
	doi = {10.1109/PLANS53410.2023.10140080},
	abstract = {This paper presents an efficient method of fusing visual and inertial data for navigation using the two-view tensor, also known as the essential matrix. The essential matrix encodes the up-to-scale geometric relationship between two camera poses and contains the relative rotation and direction-of-translation between them. A dense network of up-to-scale relative pose measurements is constructed by computing essential matrices between incoming images and a collection of past states which observed the same scene. As the essential matrix is computed online in many visual-inertial navigation systems (VINS) as part of the image processing front end, the proposed method introduces little computational overhead while avoiding all computations related to feature estimation. This approach can be viewed as a modification of the classical pose-graph simultaneous localization and mapping (SLAM) problem. This paper further presents a dynamic initialization method to bootstrap the velocity, orientation, and biases of an IMU. The initialization method makes use of the same modified pose-graph SLAM approach to solve for the up-to-scale relative poses of a window of camera frames before solving for orientation, velocity, and sensor biases. We validate the proposed methods by implementing them in Extended Kalman Filter (EKF) and nonlinear optimization forms and testing them on public datasets.},
	urldate = {2024-06-20},
	booktitle = {2023 {IEEE}/{ION} {Position}, {Location} and {Navigation} {Symposium} ({PLANS})},
	author = {Boler, Matthew and Martin, Scott},
	month = apr,
	year = {2023},
	note = {ISSN: 2153-3598},
	keywords = {Dynamics, Navigation, Simultaneous localization and mapping, Solid modeling, State estimation, Tensors, Three-dimensional displays, Visualization, sensor fusion, simultaneous localization and mapping, visual-inertial navigation},
	pages = {1341--1349},
}

This paper presents an efficient method of fusing visual and inertial data for navigation using the two-view tensor, also known as the essential matrix. The essential matrix encodes the up-to-scale geometric relationship between two camera poses and contains the relative rotation and direction-of-translation between them. A dense network of up-to-scale relative pose measurements is constructed by computing essential matrices between incoming images and a collection of past states which observed the same scene. As the essential matrix is computed online in many visual-inertial navigation systems (VINS) as part of the image processing front end, the proposed method introduces little computational overhead while avoiding all computations related to feature estimation. This approach can be viewed as a modification of the classical pose-graph simultaneous localization and mapping (SLAM) problem. This paper further presents a dynamic initialization method to bootstrap the velocity, orientation, and biases of an IMU. The initialization method makes use of the same modified pose-graph SLAM approach to solve for the up-to-scale relative poses of a window of camera frames before solving for orientation, velocity, and sensor biases. We validate the proposed methods by implementing them in Extended Kalman Filter (EKF) and nonlinear optimization forms and testing them on public datasets.

@inproceedings{givhan_comparison_2023,
	title = {Comparison of {CRPA} {Direction} of {Arrival} {Methods} on {Post} {Correlated} {GNSS} {Signals} for {Solution} {Authentication} and {Spoofing} {Detection}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=18625},
	doi = {10.33012/2023.18625},
	abstract = {Multiantenna GNSS systems allow for direction of arrival (DOA) measurements, which enable the system to estimate attitude and authenticate incoming signals. Typical multiantenna systems use meter length baselines and differenced carrier phase ranges to estimate direction of arrival. However, a controlled reception pattern antenna (CRPA) has sub carrier wavelength antenna separations, making it less than ideal for traditional DOA techniques. Instead, DOA methods from other disciplines can be applied to the GNSS signal, provided the signal is visible above the thermal noise floor. The GNSS signal is elevated above the noise floor by correlating the signal at each antenna element to recreate an GNSS baseband signal from correlator outputs that retains the original signal phase information. This work investigates three methods of direction of arrival estimation using a CRPA on post correlated GNSS signals: Multiple Signal Classification (MUSIC), Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT), and carrier phase differences. The data used to evaluate these algorithms was simulated by Orolia’s Skydel software and post processed in MATLAB. The algorithms were evaluated on runtime, measurement accuracy, and attitude accuracy for a full visible constellation in a series of tests with degrading carrier to noise density ratios (CN0). The MUSIC algorithm provided the best results at the cost of the longest runtime. However, adaptions proposed for this use case enabled significant computational savings. Next, carrier phase differences provided less accurate results but was computationally the cheapest algorithm. Finally, ESPIRIT had the least accurate results, while having a fast runtime.},
	language = {en},
	urldate = {2024-06-20},
	author = {Givhan, C. Anderson and Martin, Scott M.},
	month = jan,
	year = {2023},
	pages = {303--314},
}

Multiantenna GNSS systems allow for direction of arrival (DOA) measurements, which enable the system to estimate attitude and authenticate incoming signals. Typical multiantenna systems use meter length baselines and differenced carrier phase ranges to estimate direction of arrival. However, a controlled reception pattern antenna (CRPA) has sub carrier wavelength antenna separations, making it less than ideal for traditional DOA techniques. Instead, DOA methods from other disciplines can be applied to the GNSS signal, provided the signal is visible above the thermal noise floor. The GNSS signal is elevated above the noise floor by correlating the signal at each antenna element to recreate an GNSS baseband signal from correlator outputs that retains the original signal phase information. This work investigates three methods of direction of arrival estimation using a CRPA on post correlated GNSS signals: Multiple Signal Classification (MUSIC), Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT), and carrier phase differences. The data used to evaluate these algorithms was simulated by Orolia’s Skydel software and post processed in MATLAB. The algorithms were evaluated on runtime, measurement accuracy, and attitude accuracy for a full visible constellation in a series of tests with degrading carrier to noise density ratios (CN0). The MUSIC algorithm provided the best results at the cost of the longest runtime. However, adaptions proposed for this use case enabled significant computational savings. Next, carrier phase differences provided less accurate results but was computationally the cheapest algorithm. Finally, ESPIRIT had the least accurate results, while having a fast runtime.

@inproceedings{givhan_analysis_2023,
	title = {Analysis of an {Ionospheric} {Free} {Vector} {Tracking} {GNSS} {Software} {Defined} {Radio}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=19418},
	doi = {10.33012/2023.19418},
	abstract = {Vector tracking architectures, which utilize the user PVT estimate to track the incoming signals, have been shown to be more robust than traditional GNSS software defined radio architectures. With the recent addition of new civil signals to the GPS constellation in the L2 and L5 frequency bands, VDFLL receivers can now utilize multiple civilian GPS signals. While the appeal of frequency diversity for the vector tracking user is mostly for the added robustness to frequency-based interference, there is now also the potential for the mitigation of frequency-based PVT errors such as those caused by the ionospheric delay. Traditional receiver architectures use carrier phase measurements to remove ionospheric errors and provide precise PVT solutions, which requires the use of PLLs which are most subject to loop failure in degraded signal environments. Previous works have used the VDFLL receiver to aid phase lock loops for increased robustness or have used VDPLL architectures that rely on external aiding for RTK corrections to maintain lock. This work presents an ionospheric error corrected GPS L1 C/A and L5 VDFLL receiver that has no reliance on the weaker PLL or external aiding sources. The work outlines a receiver that provides an ionospheric corrected vector tracking range residual to the navigator for better tracking of the true position. The work also discusses the effects of the vector tracking receiver being updated from the true antenna solution rather than the ionospheric delay biased solution that corresponds to the maximization of the signal and replica correlation. The presented receiver is tested on live sky and simulated data for positioning performance in the presence of dynamics and rapidly changing received power; it shows itself to be capable of better removing frequency-based errors than compensated single frequency systems while still maintaining a level of robustness expected of vector receivers.},
	language = {en},
	urldate = {2024-06-20},
	author = {Givhan, C. Anderson and Martin, Scott M.},
	month = sep,
	year = {2023},
	pages = {3972--3981},
}

Vector tracking architectures, which utilize the user PVT estimate to track the incoming signals, have been shown to be more robust than traditional GNSS software defined radio architectures. With the recent addition of new civil signals to the GPS constellation in the L2 and L5 frequency bands, VDFLL receivers can now utilize multiple civilian GPS signals. While the appeal of frequency diversity for the vector tracking user is mostly for the added robustness to frequency-based interference, there is now also the potential for the mitigation of frequency-based PVT errors such as those caused by the ionospheric delay. Traditional receiver architectures use carrier phase measurements to remove ionospheric errors and provide precise PVT solutions, which requires the use of PLLs which are most subject to loop failure in degraded signal environments. Previous works have used the VDFLL receiver to aid phase lock loops for increased robustness or have used VDPLL architectures that rely on external aiding for RTK corrections to maintain lock. This work presents an ionospheric error corrected GPS L1 C/A and L5 VDFLL receiver that has no reliance on the weaker PLL or external aiding sources. The work outlines a receiver that provides an ionospheric corrected vector tracking range residual to the navigator for better tracking of the true position. The work also discusses the effects of the vector tracking receiver being updated from the true antenna solution rather than the ionospheric delay biased solution that corresponds to the maximization of the signal and replica correlation. The presented receiver is tested on live sky and simulated data for positioning performance in the presence of dynamics and rapidly changing received power; it shows itself to be capable of better removing frequency-based errors than compensated single frequency systems while still maintaining a level of robustness expected of vector receivers.

@incollection{lakshmanan_semi-autonomous_2023,
	address = {Cham},
	title = {Semi-autonomous {Truck} {Platooning} with a {Lean} {Sensor} {Package}},
	isbn = {9783031067808},
	url = {https://doi.org/10.1007/978-3-031-06780-8_2},
	abstract = {This chapter describes one method of approaching fuel-efficient truck platooning using a system called Cooperative Adaptive Cruise Control (CACC). The principal innovation in the system is its lean sensor package, including factory-ready standard ACC system utilizing a dual-beam radar, precision Global Positioning System (GPS), and a Vehicle-to-Vehicle (V2V) communication system. In other words, no imaging sensors such as camera or lidar, and no associated high-performance computing hardware such as Graphics Processing Units (GPU). Extensive test track and public road testing on class-8 semi-trucks, including edge case testing, reveals the efficacy and robustness of this system despite its leanness. Quantitative results are included in this chapter that trace cause and effect through the CACC system.},
	language = {en},
	urldate = {2024-06-20},
	booktitle = {{AI}-enabled {Technologies} for {Autonomous} and {Connected} {Vehicles}},
	publisher = {Springer International Publishing},
	author = {Lakshmanan, Sridhar and Adam, Cristian and Kleinow, Timothy and Richardson, Paul and Ward, Jacob and Stegner, Evan and Bevly, David and Hoffman, Mark},
	editor = {Murphey, Yi Lu and Kolmanovsky, Ilya and Watta, Paul},
	year = {2023},
	doi = {10.1007/978-3-031-06780-8_2},
	pages = {19--59},
}

This chapter describes one method of approaching fuel-efficient truck platooning using a system called Cooperative Adaptive Cruise Control (CACC). The principal innovation in the system is its lean sensor package, including factory-ready standard ACC system utilizing a dual-beam radar, precision Global Positioning System (GPS), and a Vehicle-to-Vehicle (V2V) communication system. In other words, no imaging sensors such as camera or lidar, and no associated high-performance computing hardware such as Graphics Processing Units (GPU). Extensive test track and public road testing on class-8 semi-trucks, including edge case testing, reveals the efficacy and robustness of this system despite its leanness. Quantitative results are included in this chapter that trace cause and effect through the CACC system.

@inproceedings{smith_precision_2023,
	title = {Precision {Timing} with {LEO} {Satellite} {Time} and {Location} {Signals}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=18693},
	doi = {10.33012/2023.18693},
	abstract = {The work presented in this paper aims to assess the accuracy, stability, and convergence rates of static receiver timing solutions from low-Earth orbit (LEO) Satellite Time and Location (STL) signals. The motivation for this work lies in the wide range of industries that rely on nanosecond-level timing precision. Traditional means of satellite-based timing, such as Global Navigation Satellite Systems (GNSS), prove to be vulnerable under various conditions, compromising their accuracy. The STL signals from the Iridium satellite constellation are received at a much higher signal power, rendering them more resilient to these interferences. Two tests were conducted in this study. For Test 1, two scenarios were considered. The first scenario assumes a known, static antenna position, where the receiver clock bias and drift were estimated with an Extended Kalman Filter (EKF). The second scenario assumes an unknown, static antenna position, where a 3-dimensional Earth-Centered, Earth-Fixed (ECEF) position, clock bias and clock drift were estimated with a Recursive Least Squares (RLS) Solution. The algorithms were implemented with live-sky STL data collected with a newly-released, commercially-available Jackson Labs STL-2600 receiver with a Rubidium clock input. For Test 2, a time interval difference test between the Jackson Labs receiver 1-PPS output and a GNSS 1-PPS reference. In each of the tests, the long-term timing accuracy was determined to be within 205 nanoseconds, with sub-nanosecond per second drift. The results for Test 1 include time state estimate plots, filter covariance convergence, and error statistics. The results for Test 2 include pre- and post-settling time difference plots and error statistics.},
	language = {en},
	urldate = {2024-06-20},
	author = {Smith, Austin M. and Bevly, David M.},
	month = jan,
	year = {2023},
	pages = {197--206},
}

The work presented in this paper aims to assess the accuracy, stability, and convergence rates of static receiver timing solutions from low-Earth orbit (LEO) Satellite Time and Location (STL) signals. The motivation for this work lies in the wide range of industries that rely on nanosecond-level timing precision. Traditional means of satellite-based timing, such as Global Navigation Satellite Systems (GNSS), prove to be vulnerable under various conditions, compromising their accuracy. The STL signals from the Iridium satellite constellation are received at a much higher signal power, rendering them more resilient to these interferences. Two tests were conducted in this study. For Test 1, two scenarios were considered. The first scenario assumes a known, static antenna position, where the receiver clock bias and drift were estimated with an Extended Kalman Filter (EKF). The second scenario assumes an unknown, static antenna position, where a 3-dimensional Earth-Centered, Earth-Fixed (ECEF) position, clock bias and clock drift were estimated with a Recursive Least Squares (RLS) Solution. The algorithms were implemented with live-sky STL data collected with a newly-released, commercially-available Jackson Labs STL-2600 receiver with a Rubidium clock input. For Test 2, a time interval difference test between the Jackson Labs receiver 1-PPS output and a GNSS 1-PPS reference. In each of the tests, the long-term timing accuracy was determined to be within 205 nanoseconds, with sub-nanosecond per second drift. The results for Test 1 include time state estimate plots, filter covariance convergence, and error statistics. The results for Test 2 include pre- and post-settling time difference plots and error statistics.

@unpublished{thompson_collaborative_2022,
	title = {Collaborative {Simultaneous} {Tracking} and {Navigation} with {Low} {Earth} {Orbit} {Satellite} {Signals} of {Opportunity} and {Inertial} {Navigation} {System}},
	copyright = {EMBARGO\_GLOBAL},
	url = {https://etd.auburn.edu//handle/10415/8332},
	abstract = {This thesis has not been approved for public release.},
	language = {en},
	urldate = {2024-06-25},
	author = {Thompson, Sterling},
	month = jul,
	year = {2022},
	note = {Accepted: 2022-07-26T19:59:19Z},
}

This thesis has not been approved for public release.

@unpublished{snitzer_utilization_2022,
	title = {Utilization of {Vehicle}-{Specific} {Power} as a {Powertrain} {Independent} {Platoon} {Controller} {Performance} {Metric}},
	url = {https://etd.auburn.edu//handle/10415/8517},
	abstract = {Heavy-Duty hauling faces challenges regarding the efficiency of transportation, which opens the door to new pathways to saving money while refueling via platooning.  Platooning vehicles travel together intending to reduce aerodynamic resistance during operation.  The increasing interest in autonomous solutions directs research toward applying these solutions to heavy-duty transportation.  However, autonomous solutions are a relatively new concept and require significant research before implementation on public roads.  This dilemma brings forth a new application of an emissions quantification metric called vehicle-specific power (VSP).  VSP bridges the gap between passenger vehicle emissions rates and fuel consumption.  VSP considers the total driving environment of a vehicle, which estimates powertrain effort to maintain current conditions.  The present work utilizes the powertrain effort estimation aspect of VSP rather than its emissions investigative benefits to evaluate the efficacy of Cooperative Adaptive Cruise Control (CACC).  Different controller strategies and platoon configurations are examined to determine the applicability of VSP to controller evaluation.  Experimentation was completed at the National Center for Asphalt Technology (NCAT) circuitous track, the American Center for Mobility’s (ACM) freeway loop, and a straightaway section of NCAT’s track dubbed “ideal” for platooning efficiency.  The influence of convoy position, following distance, road grade, speed, and acceleration are investigated via VSP.  VSP aims to create a more complete cost function for assessing a controller’s strategy while implementing a forward-looking evaluation technique to current controller strategies.  This cost function provides incredible insight into increasing the efficiency of an autonomously driven platoon.},
	language = {en},
	urldate = {2024-06-25},
	author = {Snitzer, Richard Philip},
	month = dec,
	year = {2022},
	note = {Accepted: 2022-12-05T20:21:25Z},
}

Heavy-Duty hauling faces challenges regarding the efficiency of transportation, which opens the door to new pathways to saving money while refueling via platooning. Platooning vehicles travel together intending to reduce aerodynamic resistance during operation. The increasing interest in autonomous solutions directs research toward applying these solutions to heavy-duty transportation. However, autonomous solutions are a relatively new concept and require significant research before implementation on public roads. This dilemma brings forth a new application of an emissions quantification metric called vehicle-specific power (VSP). VSP bridges the gap between passenger vehicle emissions rates and fuel consumption. VSP considers the total driving environment of a vehicle, which estimates powertrain effort to maintain current conditions. The present work utilizes the powertrain effort estimation aspect of VSP rather than its emissions investigative benefits to evaluate the efficacy of Cooperative Adaptive Cruise Control (CACC). Different controller strategies and platoon configurations are examined to determine the applicability of VSP to controller evaluation. Experimentation was completed at the National Center for Asphalt Technology (NCAT) circuitous track, the American Center for Mobility’s (ACM) freeway loop, and a straightaway section of NCAT’s track dubbed “ideal” for platooning efficiency. The influence of convoy position, following distance, road grade, speed, and acceleration are investigated via VSP. VSP aims to create a more complete cost function for assessing a controller’s strategy while implementing a forward-looking evaluation technique to current controller strategies. This cost function provides incredible insight into increasing the efficiency of an autonomously driven platoon.

@unpublished{mcwilliams_improving_2022,
	title = {Improving {Magnetic} {Map}-{Based} {Navigation} using {Vehicle} {Motion} {Information}},
	url = {https://etd.auburn.edu//handle/10415/8082},
	abstract = {This thesis utilizes the earth's main magnetic field as the signal for a map definition, implements a particle filter to synthesize a solution from likelihood information, and introduces vehicle motion information by means of velocity and heading measurements to augment the traditional filter structure. Three different process models are investigated: Gauss-Markov, a known capable technique in which particles evolve stochastically; wheel speed linear motion with magnetometer heading updates, in which the particles attempt to imitate the movement of the vehicle using a heading derived from magnetic north (with declination correction); and wheel speed linear motion with gyroscope heading updates, in which angular velocity measurements are integrated to update the heading at every time step instead. Measurement updates were performed with respect to the map and the local magnetic signal. Two nominal routes were evaluated using the Gauss-Markov approach as a baseline and the root-mean-square error in the position estimate compared to that of the motion-informed models. Results show that vehicle odometry can decrease the error in the position solution by between 22\% and 77\% on average and decrease the typical maximum error along a route by about 54\%. This focus was expanded to explore non-nominal driving conditions including a map driven in reverse, a map featuring a short detour, and a map featuring a large detour. In these cases, every filter implementation struggled to track the vehicle once it exited the map, but recovery was possible in some instances when the vehicle returned to a known or strongly identifiable region.},
	language = {en},
	urldate = {2024-06-25},
	author = {McWilliams, Ryan},
	month = jan,
	year = {2022},
	note = {Accepted: 2022-01-06T14:33:54Z},
}

This thesis utilizes the earth's main magnetic field as the signal for a map definition, implements a particle filter to synthesize a solution from likelihood information, and introduces vehicle motion information by means of velocity and heading measurements to augment the traditional filter structure. Three different process models are investigated: Gauss-Markov, a known capable technique in which particles evolve stochastically; wheel speed linear motion with magnetometer heading updates, in which the particles attempt to imitate the movement of the vehicle using a heading derived from magnetic north (with declination correction); and wheel speed linear motion with gyroscope heading updates, in which angular velocity measurements are integrated to update the heading at every time step instead. Measurement updates were performed with respect to the map and the local magnetic signal. Two nominal routes were evaluated using the Gauss-Markov approach as a baseline and the root-mean-square error in the position estimate compared to that of the motion-informed models. Results show that vehicle odometry can decrease the error in the position solution by between 22% and 77% on average and decrease the typical maximum error along a route by about 54%. This focus was expanded to explore non-nominal driving conditions including a map driven in reverse, a map featuring a short detour, and a map featuring a large detour. In these cases, every filter implementation struggled to track the vehicle once it exited the map, but recovery was possible in some instances when the vehicle returned to a known or strongly identifiable region.

@unpublished{kamrath_computer_2022,
	title = {Computer {Vision} {Based} {Cooperative} {Navigation} for {UAVs} and {Ground} {Vehicles}},
	url = {https://etd.auburn.edu//handle/10415/8268},
	abstract = {This thesis is not approved for public release.},
	language = {en},
	urldate = {2024-06-25},
	author = {Kamrath, Daniel},
	month = jun,
	year = {2022},
	note = {Accepted: 2022-06-30T20:41:48Z},
}

This thesis is not approved for public release.

@article{jones_collaborative_2022,
	title = {Collaborative {Architectures} for {Relative} {Position} {Estimation} of {Ground} {Vehicles} with {UWB} {Ranging} and {Vehicle} {Dynamic} {Models}},
	url = {https://etd.auburn.edu//handle/10415/8556},
	abstract = {The relative position to neighboring vehicles is critical to ongoing autonomy efforts including
collision avoidance and path planning; therefore, it should not be fully dependent
on an external reference such as GPS. This thesis presents methods for real-time relative
positioning of ground vehicles by employing a network of on-board ultra-wideband (UWB)
radios. The difficulties in range-based relative positioning, and the results from prior literature
are described. Next, the proposed methods are derived which employ the kinematic
bicycle model to constrain the estimated states to align with ground vehicle dynamics.
The initial methods do not require vehicle-to-vehicle (V2V) communication. However,
cooperative methods are also explored which make use of the simultaneous ranging and
communication capabilities of UWBs. Feedback of the tracked vehicle’s dynamic states
(velocity, yaw-rate, and steer angle) are analyzed for their impact on estimation quality.
A geometrically-inspired consensus extended Kalman filter (CEKF) is also developed as a
modification to both the prior work and the proposed vehicle-dynamic EKF (VehDynEKF).
The methods developed in this thesis improve upon prior literature results in accuracy
and robustness in the presence of UWB measurement errors, unfavorable relative geometry,
and dynamic maneuvers. While the CEKF shows improvement over the prior literature
methods without additional sensors, it under performs the VehDynEKF proposed here. With
only the use of UWB ranging and odometry, the VehDynEKF in this thesis can provide robust
relative pose estimates to a neighboring vehicle. The estimate is affected by relative dynamics
but maintains a mean error less than 2.5 meters in both simulation and experimental results
without cooperative feedback. The lateral velocity of the vehicles is found to be a primary
contributor to error; odometry including measurements of the estimating vehicle’s lateral
velocity significantly improves the results. Lastly, if the ego vehicle has access to the tracked vehicle’s longitudinal velocity, the mean error is refined to be less than 1 meter—sufficient
for the majority of safety-critical applications.},
	language = {en},
	urldate = {2024-06-25},
	author = {Jones, Benjamin},
	month = dec,
	year = {2022},
	note = {Accepted: 2022-12-09T19:20:55Z},
}

The relative position to neighboring vehicles is critical to ongoing autonomy efforts including collision avoidance and path planning; therefore, it should not be fully dependent on an external reference such as GPS. This thesis presents methods for real-time relative positioning of ground vehicles by employing a network of on-board ultra-wideband (UWB) radios. The difficulties in range-based relative positioning, and the results from prior literature are described. Next, the proposed methods are derived which employ the kinematic bicycle model to constrain the estimated states to align with ground vehicle dynamics. The initial methods do not require vehicle-to-vehicle (V2V) communication. However, cooperative methods are also explored which make use of the simultaneous ranging and communication capabilities of UWBs. Feedback of the tracked vehicle’s dynamic states (velocity, yaw-rate, and steer angle) are analyzed for their impact on estimation quality. A geometrically-inspired consensus extended Kalman filter (CEKF) is also developed as a modification to both the prior work and the proposed vehicle-dynamic EKF (VehDynEKF). The methods developed in this thesis improve upon prior literature results in accuracy and robustness in the presence of UWB measurement errors, unfavorable relative geometry, and dynamic maneuvers. While the CEKF shows improvement over the prior literature methods without additional sensors, it under performs the VehDynEKF proposed here. With only the use of UWB ranging and odometry, the VehDynEKF in this thesis can provide robust relative pose estimates to a neighboring vehicle. The estimate is affected by relative dynamics but maintains a mean error less than 2.5 meters in both simulation and experimental results without cooperative feedback. The lateral velocity of the vehicles is found to be a primary contributor to error; odometry including measurements of the estimating vehicle’s lateral velocity significantly improves the results. Lastly, if the ego vehicle has access to the tracked vehicle’s longitudinal velocity, the mean error is refined to be less than 1 meter—sufficient for the majority of safety-critical applications.

@unpublished{campos-vega_investigation_2022,
	title = {Investigation of {Precise} {Relative} {Positioning} through {Varying} {Equipment} {Grades}},
	url = {https://etd.auburn.edu//handle/10415/8094},
	abstract = {In this thesis, three methodologies are investigated in order to provide precise relative positioning knowledge between two dynamic platforms as equipment grade is varied. Two methods are integrated into the real-time kinematic (RTK) algorithm using differential GPS techniques to aid the ambiguity resolution of static and dynamic baselines. Lastly, with the introduction of modern GNSS signals, the benefits of integrating single-frequency (SF) observables from GPS, Galileo (GAL), and the BeiDou (BDS) constellations into a single RTK algorithm is explored. The first method uses an adaptive extended Kalman Filter (EKF) to estimate stochastic properties of single-differenced (SD) GPS combinations. This technique improves the resolution of the carrier-phase ambiguities allowing for precise relative navigation and improved time-to-first fix (TTFF). Secondly, a tightly-coupled RTK algorithm is demonstrated which combines ultra-wideband radio (UWB) observables with SD GPS combinations. This is shown to improve TTFF and increase the robustness of the fixed integer solution. An overview of the estimation techniques is provided, and errors observed in diagnostic assessment tools are explained. To better evaluate the robustness of the presented algorithms, they are applied to experimental data collected with equipment of varying grade. Survey-grade equipment is heavily used in RTK research or in applications with a need for precise relative positioning between a base and rover platform. This equipment can be costly and not applicable to many emerging modular technologies. Low-cost sensor suites have been shown to create noisier observables due to the instabilities of their internal oscillators. In addition, low-cost antennas exhibit irregular gain patterns and poor multi-path suppression which obscure the ambiguity search space leading to longer TTFF and higher chances of incorrectly fixing integers. Thus, it is of interest to evaluate the effects of  equipment grade on the ambiguity search space for on-the-fly ambiguity estimation. The investigation of the search space is first assessed using a zero-baseline test. This test provides insight into the observability of the carrier phase ambiguity since no geometric range is embedded in the observables. The study then continues by evaluating the search space during a static baseline test. Measurement innovations are monitored and a unique integer validation scheme is shown to improve the percentage of correct integer fixes for all utilized equipment. Lastly, the RTK algorithm is extended to consider dynamic baselines under the pretense that both the base and rover platforms are mobile. This breaks several assumptions of the nominal RTK algorithm and allows it to be considered a Dynamic-Real Time Kinematic (DRTK) algorithm.},
	language = {en},
	urldate = {2024-06-25},
	author = {Campos-Vega, Christian},
	month = feb,
	year = {2022},
	note = {Accepted: 2022-02-22T20:05:36Z},
}

In this thesis, three methodologies are investigated in order to provide precise relative positioning knowledge between two dynamic platforms as equipment grade is varied. Two methods are integrated into the real-time kinematic (RTK) algorithm using differential GPS techniques to aid the ambiguity resolution of static and dynamic baselines. Lastly, with the introduction of modern GNSS signals, the benefits of integrating single-frequency (SF) observables from GPS, Galileo (GAL), and the BeiDou (BDS) constellations into a single RTK algorithm is explored. The first method uses an adaptive extended Kalman Filter (EKF) to estimate stochastic properties of single-differenced (SD) GPS combinations. This technique improves the resolution of the carrier-phase ambiguities allowing for precise relative navigation and improved time-to-first fix (TTFF). Secondly, a tightly-coupled RTK algorithm is demonstrated which combines ultra-wideband radio (UWB) observables with SD GPS combinations. This is shown to improve TTFF and increase the robustness of the fixed integer solution. An overview of the estimation techniques is provided, and errors observed in diagnostic assessment tools are explained. To better evaluate the robustness of the presented algorithms, they are applied to experimental data collected with equipment of varying grade. Survey-grade equipment is heavily used in RTK research or in applications with a need for precise relative positioning between a base and rover platform. This equipment can be costly and not applicable to many emerging modular technologies. Low-cost sensor suites have been shown to create noisier observables due to the instabilities of their internal oscillators. In addition, low-cost antennas exhibit irregular gain patterns and poor multi-path suppression which obscure the ambiguity search space leading to longer TTFF and higher chances of incorrectly fixing integers. Thus, it is of interest to evaluate the effects of equipment grade on the ambiguity search space for on-the-fly ambiguity estimation. The investigation of the search space is first assessed using a zero-baseline test. This test provides insight into the observability of the carrier phase ambiguity since no geometric range is embedded in the observables. The study then continues by evaluating the search space during a static baseline test. Measurement innovations are monitored and a unique integer validation scheme is shown to improve the percentage of correct integer fixes for all utilized equipment. Lastly, the RTK algorithm is extended to consider dynamic baselines under the pretense that both the base and rover platforms are mobile. This breaks several assumptions of the nominal RTK algorithm and allows it to be considered a Dynamic-Real Time Kinematic (DRTK) algorithm.

@unpublished{burchfield_multi-antenna_2022,
	title = {A {Multi}-{Antenna} {Vector} {Tracking} {Beamsteering} {GPS} {Receiver} for {Robust} {Positioning}},
	url = {https://etd.auburn.edu//handle/10415/8243},
	abstract = {This thesis proposes the coupling of a Global Positioning System (GPS) L1 C/A vector tracking software-defined receiver with controlled reception pattern array array (CRPA) satellite constrained beamsteering, i.e. a multi-antenna high-gain vector tracking receiver. As technology advances, the number of systems relying on Global Navigation Satellite Systems' (GNSS) precise positioning and timing is increasing. Improvements in robustness and overall design are necessary for receivers to estimate position, velocity, and time accurately in all environments. This work is inspired by previous receiver designs by NAVSYS and the German Aerospace Center (DLR). The proposed receiver conducts pre-correlator beamsteering. Pre-correlator beamsteering is lower SWaP-C as it reduces the number of receiver correlator channels compared to DLR's post-correlator implementation. The vector tracking receiver feeds back attitude corrected satellite geometry to a beamsteering module that updates the beam constraints as vector tracking's extended Kalman filter (EKF) applies corrections. The proposed receiver is compared to a multi-antenna scalar tracking receiver in all testing scenarios. Comparisons are also made with a single-antenna vector tracking receiver, a single-antenna scalar tracking receiver, and a commercial-off-the-shelf (COTS) receiver. In simulation, receiver performance using a range from one to eight element CRPAs is compared to understand the benefits different arrays offer to receiver design. The simulations show there is a diminishing return in signal quality improvements as the number of elements increase. The simulations also show that a seven and eight element implemented vector tracking receiver can track signals at carrier-to-noise ratios as low as 12 dB-Hz, which is much lower than previously documented tracking thresholds. The proposed receiver outperforms the other receivers when the simulation scenarios are noisy, improving PVT estimates considerably. Four element configurations of the receivers are tested with dynamic live sky collected data. The multi-antenna high-gain vector tracking receiver outperforms the other receiver designs, aligning closely with the COTS receiver. The multi-antenna high-gain vector tracking receiver’s performance is followed by the single-antenna vector tracking receiver, the multi-antenna scalar tracking receiver, and the single-antenna scalar tracking receiver, respectively. The receivers are also tested in a jamming environment. The proposed receiver offers a four dB improvement in jamming resilience compared to the single-antenna vector tracking receiver.},
	language = {en},
	urldate = {2024-06-25},
	author = {Burchfield, Scott},
	month = may,
	year = {2022},
	note = {Accepted: 2022-05-17T21:19:30Z},
}

This thesis proposes the coupling of a Global Positioning System (GPS) L1 C/A vector tracking software-defined receiver with controlled reception pattern array array (CRPA) satellite constrained beamsteering, i.e. a multi-antenna high-gain vector tracking receiver. As technology advances, the number of systems relying on Global Navigation Satellite Systems' (GNSS) precise positioning and timing is increasing. Improvements in robustness and overall design are necessary for receivers to estimate position, velocity, and time accurately in all environments. This work is inspired by previous receiver designs by NAVSYS and the German Aerospace Center (DLR). The proposed receiver conducts pre-correlator beamsteering. Pre-correlator beamsteering is lower SWaP-C as it reduces the number of receiver correlator channels compared to DLR's post-correlator implementation. The vector tracking receiver feeds back attitude corrected satellite geometry to a beamsteering module that updates the beam constraints as vector tracking's extended Kalman filter (EKF) applies corrections. The proposed receiver is compared to a multi-antenna scalar tracking receiver in all testing scenarios. Comparisons are also made with a single-antenna vector tracking receiver, a single-antenna scalar tracking receiver, and a commercial-off-the-shelf (COTS) receiver. In simulation, receiver performance using a range from one to eight element CRPAs is compared to understand the benefits different arrays offer to receiver design. The simulations show there is a diminishing return in signal quality improvements as the number of elements increase. The simulations also show that a seven and eight element implemented vector tracking receiver can track signals at carrier-to-noise ratios as low as 12 dB-Hz, which is much lower than previously documented tracking thresholds. The proposed receiver outperforms the other receivers when the simulation scenarios are noisy, improving PVT estimates considerably. Four element configurations of the receivers are tested with dynamic live sky collected data. The multi-antenna high-gain vector tracking receiver outperforms the other receiver designs, aligning closely with the COTS receiver. The multi-antenna high-gain vector tracking receiver’s performance is followed by the single-antenna vector tracking receiver, the multi-antenna scalar tracking receiver, and the single-antenna scalar tracking receiver, respectively. The receivers are also tested in a jamming environment. The proposed receiver offers a four dB improvement in jamming resilience compared to the single-antenna vector tracking receiver.

@unpublished{boler_observability-informed_2022,
	title = {Observability-{Informed} {Measurement} {Validation} for {Visual}-{Inertial} {Navigation}},
	url = {https://etd.auburn.edu//handle/10415/8218},
	abstract = {This thesis presents a measurement validation method for visual-inertial navigation and an
implementation of a visual-inertial estimator which makes use of it. Many autonomous plat-
forms, especially flying ones, rely on accurate and reliable state estimates from a visual-inertial
estimator to maintain safe and controlled flight towards a goal. The measurement validation
method presented in this thesis makes use of a geometric analysis of the landmark measuremnt
model to enable early and reliable validation, safely integrating high-quality measurements
into the state estimation process. First, the IMU and camera sensors are detailed along with
the sensor processing techniques necessary to make use of them. Next, a detailed description
of two standard visual-inertial estimation approaches is presented to develop necessary back-
ground knowledge. Following these descriptions, an analysis of the relationships between the
geometry of landmark observation and the accuracy and reliability of landmark estimates is per-
formed, concluding with the proposal of a new validation method which delays measurement
processing until the landmark is predicted to be observable. Lastly, a visual-inertial estimator is
developed which makes use of the proposed method and tested on the EUROC dataset, the most
common visual-inertial dataset, against several state-of-the-art estimators. In this comparison,
the proposed estimator demonstrates competitive performace, reliably producing positioning
errors of less than 0.5 meters over flights up to 120 meters long. Overall, the proposed method
is demonstrated to be reliable and accurate in competition with significantly more advanced
and complicated estimators.},
	language = {en},
	urldate = {2024-06-25},
	author = {Boler, Matthew},
	month = may,
	year = {2022},
	note = {Accepted: 2022-05-04T16:19:36Z},
}

This thesis presents a measurement validation method for visual-inertial navigation and an implementation of a visual-inertial estimator which makes use of it. Many autonomous plat- forms, especially flying ones, rely on accurate and reliable state estimates from a visual-inertial estimator to maintain safe and controlled flight towards a goal. The measurement validation method presented in this thesis makes use of a geometric analysis of the landmark measuremnt model to enable early and reliable validation, safely integrating high-quality measurements into the state estimation process. First, the IMU and camera sensors are detailed along with the sensor processing techniques necessary to make use of them. Next, a detailed description of two standard visual-inertial estimation approaches is presented to develop necessary back- ground knowledge. Following these descriptions, an analysis of the relationships between the geometry of landmark observation and the accuracy and reliability of landmark estimates is per- formed, concluding with the proposal of a new validation method which delays measurement processing until the landmark is predicted to be observable. Lastly, a visual-inertial estimator is developed which makes use of the proposed method and tested on the EUROC dataset, the most common visual-inertial dataset, against several state-of-the-art estimators. In this comparison, the proposed estimator demonstrates competitive performace, reliably producing positioning errors of less than 0.5 meters over flights up to 120 meters long. Overall, the proposed method is demonstrated to be reliable and accurate in competition with significantly more advanced and complicated estimators.

@unpublished{ward_methods_2022,
	title = {Methods of {Optimal} {Control} for {Fuel} {Efficient} {Class}-8 {Vehicle} {Platoons} {Over} {Uneven} {Terrain}},
	url = {https://etd.auburn.edu//handle/10415/8431},
	abstract = {This thesis implements an NMPC control system to facilitate fuel-optimal platooning of
class-8 vehicles over challenging terrain. Prior research has shown that Cooperative Adaptive
Cruise Control (CACC), which allows multiple class 8 vehicles to follow in close proximity,
can save between 3-8\% in overall fuel consumption on flat terrain. However, on more challenging
terrain, e.g. rolling hills, platooning vehicles can experience diminished fuel savings,
and, in some cases, an increase in fuel consumption relative to individual vehicle operation.
This research explores the use of Nonlinear Model Predictive Control (NMPC) with
pre-defined route grade profiles to allow platooning vehicles to generate an optimal velocity
trajectory with respect to fuel-consumption. In order to successfully implement the NMPC
system, a model relating vehicle-velocity to fuel-consumption was generated and validated
using experimental data. Additionally, the pre-defined route grade profiles were created by
differencing a vehicles GPS-velocity over the desired terrain profile. The real-time NMPC
system was then implemented on a two-truck platoon operating over challenging terrain,
with a reference vehicle running individually. The results from NMPC platooning are compared
against classical proportional-integral-derivative (PID) platooning methods to obtain
comparative fuel-savings and energy efficiency. In the final analysis, significant fuel savings of
greater than 14\&20\% were seen for the lead and following vehicles relative to their respective
traditional cruise-control and platooning architectures.},
	language = {en},
	urldate = {2024-06-25},
	author = {Ward, Jacob},
	month = aug,
	year = {2022},
	note = {Accepted: 2022-08-18T20:33:59Z},
}

This thesis implements an NMPC control system to facilitate fuel-optimal platooning of class-8 vehicles over challenging terrain. Prior research has shown that Cooperative Adaptive Cruise Control (CACC), which allows multiple class 8 vehicles to follow in close proximity, can save between 3-8% in overall fuel consumption on flat terrain. However, on more challenging terrain, e.g. rolling hills, platooning vehicles can experience diminished fuel savings, and, in some cases, an increase in fuel consumption relative to individual vehicle operation. This research explores the use of Nonlinear Model Predictive Control (NMPC) with pre-defined route grade profiles to allow platooning vehicles to generate an optimal velocity trajectory with respect to fuel-consumption. In order to successfully implement the NMPC system, a model relating vehicle-velocity to fuel-consumption was generated and validated using experimental data. Additionally, the pre-defined route grade profiles were created by differencing a vehicles GPS-velocity over the desired terrain profile. The real-time NMPC system was then implemented on a two-truck platoon operating over challenging terrain, with a reference vehicle running individually. The results from NMPC platooning are compared against classical proportional-integral-derivative (PID) platooning methods to obtain comparative fuel-savings and energy efficiency. In the final analysis, significant fuel savings of greater than 14&20% were seen for the lead and following vehicles relative to their respective traditional cruise-control and platooning architectures.

@unpublished{pierce_graph-based_2022,
	title = {Graph-{Based} {Relative} {Path} {Estimation} {Using} {Landmarks} for {Long} {Distance} {Ground} {Vehicle} {Following}},
	url = {https://etd.auburn.edu//handle/10415/8542},
	abstract = {This dissertation presents a graph-based sensor fusion framework for the localization of automated ground vehicles for leader-follower path duplication. A specific focus is given to scenarios where the following distance between vehicles is high. Localization accuracy is critical for any automated path following task. While high localization accuracy can be achieved using GPS corrections or a priori maps, these resources are not available in certain scenarios such as remote areas with limited infrastructure and a priori information. In this dissertation, a novel method is proposed for solving this localization problem that does not depend on built infrastructure or a priori information. A graph-based framework is used to estimate the path taken by the lead vehicle using relative measurements of differential GPS between vehicles, odometry from onboard sensor measurements, and exchanged landmark observations.
     The graph-based estimation framework developed in this dissertation allows for ad-hoc, nonlinear measurements for estimating a near-optimal path solution. Each sensor input provides complementary benefits: differential GPS allows for centimeter-level accuracy, vehicle odometry allows for spanning GPS outages and gaps in landmarks, and landmark observations bound path errors with respect to following distance. The findings of an observability analysis are presented to show failure conditions for certain vehicle and landmark configurations. A simulation study is developed and used to demonstrate the success of the proposed method and characterize the estimator’s performance in a number of controlled scenarios. The findings from the simulation study are validated with experimental data from a pair of Class 8 tractor-trailers, each equipped with a GPS receiver, a multi-channel lidar, wheel encoders, an inertial measurement unit, and a Dedicated Short Range Communications (DSRC) radio.
     An overview is presented for each method used to generate the measurements used in the graph-based estimator. This includes an overview and error characterization of Time Differenced Carrier Phase (TDCP) and Dynamic-Base RTK (DRTK) used for precise odometry and inter-vehicle relative positions, respectively. An odometry model is provided for determining vehicle motion from wheel speed and yaw rate sensors. Additionally, two unique approaches are presented for detecting road sign and pole-like objects from 3D point cloud data for use as landmark observations.
     Results show that the presented method improves performance when compared to existing methods in terms of both accuracy and availability. Compared to many existing map-matching approaches, the presented approach requires a relatively small number of landmarks ({\textasciitilde}11 per km) to achieve the accuracy target regardless of GPS availability. Under nominal conditions, the presented method is successful in meeting the estimation accuracy required for path control with average lateral path position errors of 0.94 cm and path orientation errors of 0.14 degrees. It is also shown that the path errors remain bounded with respect to following distance when a sufficient number of landmarks are present, allowing for large gaps between vehicles.},
	language = {en},
	urldate = {2024-06-25},
	author = {Pierce, Dan},
	month = dec,
	year = {2022},
	note = {Accepted: 2022-12-08T14:17:59Z},
}

This dissertation presents a graph-based sensor fusion framework for the localization of automated ground vehicles for leader-follower path duplication. A specific focus is given to scenarios where the following distance between vehicles is high. Localization accuracy is critical for any automated path following task. While high localization accuracy can be achieved using GPS corrections or a priori maps, these resources are not available in certain scenarios such as remote areas with limited infrastructure and a priori information. In this dissertation, a novel method is proposed for solving this localization problem that does not depend on built infrastructure or a priori information. A graph-based framework is used to estimate the path taken by the lead vehicle using relative measurements of differential GPS between vehicles, odometry from onboard sensor measurements, and exchanged landmark observations. The graph-based estimation framework developed in this dissertation allows for ad-hoc, nonlinear measurements for estimating a near-optimal path solution. Each sensor input provides complementary benefits: differential GPS allows for centimeter-level accuracy, vehicle odometry allows for spanning GPS outages and gaps in landmarks, and landmark observations bound path errors with respect to following distance. The findings of an observability analysis are presented to show failure conditions for certain vehicle and landmark configurations. A simulation study is developed and used to demonstrate the success of the proposed method and characterize the estimator’s performance in a number of controlled scenarios. The findings from the simulation study are validated with experimental data from a pair of Class 8 tractor-trailers, each equipped with a GPS receiver, a multi-channel lidar, wheel encoders, an inertial measurement unit, and a Dedicated Short Range Communications (DSRC) radio. An overview is presented for each method used to generate the measurements used in the graph-based estimator. This includes an overview and error characterization of Time Differenced Carrier Phase (TDCP) and Dynamic-Base RTK (DRTK) used for precise odometry and inter-vehicle relative positions, respectively. An odometry model is provided for determining vehicle motion from wheel speed and yaw rate sensors. Additionally, two unique approaches are presented for detecting road sign and pole-like objects from 3D point cloud data for use as landmark observations. Results show that the presented method improves performance when compared to existing methods in terms of both accuracy and availability. Compared to many existing map-matching approaches, the presented approach requires a relatively small number of landmarks (~11 per km) to achieve the accuracy target regardless of GPS availability. Under nominal conditions, the presented method is successful in meeting the estimation accuracy required for path control with average lateral path position errors of 0.94 cm and path orientation errors of 0.14 degrees. It is also shown that the path errors remain bounded with respect to following distance when a sufficient number of landmarks are present, allowing for large gaps between vehicles.

@inproceedings{snitzer_experimentally_2022,
	title = {Experimentally {Establishing} {Ideal} {Platooning} {Performance} as a {Metric} for {Real}-{World} {Platooning} {Assessment}},
	url = {https://www.sae.org/publications/technical-papers/content/2022-01-0069/},
	abstract = {Platooning heavy-duty trucks decreases aerodynamic drag for following trucks, reducing energy consumption, and increasing both range and mileage. Previous platooning experimentation has demonstrated fuel economy benefits in two-, three-, and four-truck configurations. However, exogenous variables di},
	language = {English},
	urldate = {2024-06-20},
	author = {Snitzer, Philip and Stegner, Evan and Siefert, Jan and Bevly, David M. and Hoffman, Mark},
	month = mar,
	year = {2022},
	doi = {10.4271/2022-01-0069},
}

Platooning heavy-duty trucks decreases aerodynamic drag for following trucks, reducing energy consumption, and increasing both range and mileage. Previous platooning experimentation has demonstrated fuel economy benefits in two-, three-, and four-truck configurations. However, exogenous variables di

@inproceedings{meyer_cluster-based_2022,
	series = {2nd {Modeling}, {Estimation} and {Control} {Conference} {MECC} 2022},
	title = {Cluster-{Based} {Wall} {Curvature} {Detection} and {Parameterization} for {Autonomous} {Racing} using {LiDAR} {Point} {Clouds}},
	volume = {55},
	url = {https://www.sciencedirect.com/science/article/pii/S2405896322028749},
	doi = {10.1016/j.ifacol.2022.11.231},
	abstract = {Auotonomous driving and robotic operations often involve and rely upon road edge detection from perception sensor data. In autonomous racing, an emerging application which is currently driving high-dynamic algorithm development in the field of autonomy, edge detection provides safety for the system by making impending wall collisions detectable and offering an aid to on-track localization and guidance. An algorithm is here proposed for the detection of curved and straight wall sections from LiDAR data in race track environments. This method is unique in leveraging point clustering for wall detections, and is designed to provide mid-process results to be used both in this wall detection task as well as in further object detection processes as part of a cohesive perception stack. Position-aware outlier reduction and a least-squares parabolic line fit are used to clean and parameterize the wall position, orientation, and curvature results within individual frames of point cloud data. The algorithm was tested over 200 frames of data with an RMS lateral offset error of the parameterized wall of 0.11 meters.},
	urldate = {2024-06-20},
	booktitle = {{IFAC}-{PapersOnLine}},
	author = {Meyer, Stephanie W. and Bevly, David M.},
	month = jan,
	year = {2022},
	pages = {494--499},
}

Auotonomous driving and robotic operations often involve and rely upon road edge detection from perception sensor data. In autonomous racing, an emerging application which is currently driving high-dynamic algorithm development in the field of autonomy, edge detection provides safety for the system by making impending wall collisions detectable and offering an aid to on-track localization and guidance. An algorithm is here proposed for the detection of curved and straight wall sections from LiDAR data in race track environments. This method is unique in leveraging point clustering for wall detections, and is designed to provide mid-process results to be used both in this wall detection task as well as in further object detection processes as part of a cohesive perception stack. Position-aware outlier reduction and a least-squares parabolic line fit are used to clean and parameterize the wall position, orientation, and curvature results within individual frames of point cloud data. The algorithm was tested over 200 frames of data with an RMS lateral offset error of the parameterized wall of 0.11 meters.

@inproceedings{jones_ground-vehicle_2022,
	series = {2nd {Modeling}, {Estimation} and {Control} {Conference} {MECC} 2022},
	title = {Ground-{Vehicle} {Relative} {Position} {Estimation} with {UWB} {Ranges} and a {Vehicle} {Dynamics} {Model}},
	volume = {55},
	url = {https://www.sciencedirect.com/science/article/pii/S2405896322029044},
	doi = {10.1016/j.ifacol.2022.11.261},
	abstract = {An accurate relative position vector (RPV) solution between local vehicles is critical in numerous autonomous vehicle applications from cooperative cruise control (CACC) to commercial truck platooning. Relative GPS solutions can deliver sufficient accuracy for such applications, but resiliency and availability can suffer in cluttered environments; thus, relative position solutions independent of GPS are necessary. Ultra-wideband (UWB) radios can provide accurate and robust range, and have gathered attention in recent decades for use in navigation. Prior work has shown that relative position estimation of dynamic vehicles is possible without a GPS reference through UWB-ranging and a constant-velocity Extended Kalman Filter (EKF). Through a kinematic bicycle model, this work modifies the state vector to include direct estimates of the lead vehicle's longitudinal speed and effective steer angle. This improves estimation quality and robustness in the presence of UWB measurement errors, unfavorable relative geometry, and dynamic maneuvers. The algorithm has been compared to previous methods in simulation and experimental testing environments and exhibits both superior accuracy as well as improved robustness during periods of difficult relative geometry.},
	urldate = {2024-06-20},
	booktitle = {{IFAC}-{PapersOnLine}},
	author = {Jones, Ben and Thompson, Kyle and Pierce, Dan and Martin, Scott and Bevly, David},
	month = jan,
	year = {2022},
	keywords = {Kalman filtering, Relative position estimation, ultra-wideband radios, vehicle dynamics},
	pages = {681--687},
}

An accurate relative position vector (RPV) solution between local vehicles is critical in numerous autonomous vehicle applications from cooperative cruise control (CACC) to commercial truck platooning. Relative GPS solutions can deliver sufficient accuracy for such applications, but resiliency and availability can suffer in cluttered environments; thus, relative position solutions independent of GPS are necessary. Ultra-wideband (UWB) radios can provide accurate and robust range, and have gathered attention in recent decades for use in navigation. Prior work has shown that relative position estimation of dynamic vehicles is possible without a GPS reference through UWB-ranging and a constant-velocity Extended Kalman Filter (EKF). Through a kinematic bicycle model, this work modifies the state vector to include direct estimates of the lead vehicle's longitudinal speed and effective steer angle. This improves estimation quality and robustness in the presence of UWB measurement errors, unfavorable relative geometry, and dynamic maneuvers. The algorithm has been compared to previous methods in simulation and experimental testing environments and exhibits both superior accuracy as well as improved robustness during periods of difficult relative geometry.

@inproceedings{steadman_teleoperated_2022,
	title = {{TELEOPERATED} {GROUND} {VEHICLE} {ROLLOVER} {PREVENTION} {VIA} {HAPTIC} {FEEDBACK} {OF} {THE} {ZERO}-{MOMENT} {POINT} {INDEX}},
	abstract = {Many rollover prevention algorithms rely on vehicle models which are difficult to develop and require extensive knowledge of the vehicle. The Zero-Moment Point (ZMP) combines a simple vehicle model with IMU-only sensor measurements. When used in conjunction with haptic feedback, ground vehicle rollover can be prevented. This paper investigates IMU grade requirements for an accurate rollover prediction. This paper also discusses a haptic feedback design that delivers operator alerts to prevent rollover. An experiment was conducted using a Gazebo simulation to assess the capabilities of the ZMP method to predict vehicle wheel lift-off and demonstrate the potential for haptic communication of the ZMP index to prevent rollover.},
	language = {en},
	author = {Steadman, Kathleen and Stubbs, Chandler and Baskaran, Avinash and Rose, Chad G and Bevly, David},
	year = {2022},
}

Many rollover prevention algorithms rely on vehicle models which are difficult to develop and require extensive knowledge of the vehicle. The Zero-Moment Point (ZMP) combines a simple vehicle model with IMU-only sensor measurements. When used in conjunction with haptic feedback, ground vehicle rollover can be prevented. This paper investigates IMU grade requirements for an accurate rollover prediction. This paper also discusses a haptic feedback design that delivers operator alerts to prevent rollover. An experiment was conducted using a Gazebo simulation to assess the capabilities of the ZMP method to predict vehicle wheel lift-off and demonstrate the potential for haptic communication of the ZMP index to prevent rollover.

@inproceedings{hilyer_vehicle_2022,
	address = {Warrendale, PA},
	title = {Vehicle {Load} {Estimation} {Using} {Recursive} {Total} {Least} {Squares} for {Rollover} {Detection}},
	url = {https://www.sae.org/publications/technical-papers/content/2022-01-0914/},
	abstract = {This paper will describe the development of a load estimation algorithm that is used to estimate the load parameters necessary to detect a vehicle’s proximity to rollover. When operating a vehicle near its handling limits or with large loads, vehicle rollover must be considered for safe operation. V},
	language = {English},
	urldate = {2024-06-20},
	publisher = {SAE Technical Paper},
	author = {Hilyer, Trenton and Bevly, David M.},
	month = mar,
	year = {2022},
	doi = {10.4271/2022-01-0914},
}

This paper will describe the development of a load estimation algorithm that is used to estimate the load parameters necessary to detect a vehicle’s proximity to rollover. When operating a vehicle near its handling limits or with large loads, vehicle rollover must be considered for safe operation. V

@inproceedings{stegner_new_2022,
	address = {Warrendale, PA},
	title = {New {Metrics} for {Quantifying} the {Energy} {Efficiency} of {Platoons} in the {Presence} of {Disturbances}},
	url = {https://www.sae.org/publications/technical-papers/content/2022-01-0526/},
	abstract = {Due to aerodynamic drag reduction, vehicles may have significant energy savings while platooning in close succession. However, when circumstances force active deceleration to maintain the platoon, such as during vehicle cut-ins or grade changes, the aerodynamic efficiency benefits may be undermined},
	language = {English},
	urldate = {2024-06-20},
	publisher = {SAE Technical Paper},
	author = {Stegner, Evan and Snitzer, Philip and Bevly, David and Hoffman, Mark},
	month = mar,
	year = {2022},
	doi = {10.4271/2022-01-0526},
}

Due to aerodynamic drag reduction, vehicles may have significant energy savings while platooning in close succession. However, when circumstances force active deceleration to maintain the platoon, such as during vehicle cut-ins or grade changes, the aerodynamic efficiency benefits may be undermined

@inproceedings{carrillo_advanced_2022,
	title = {Advanced high-fidelity autonomy systems simulation},
	volume = {12115},
	url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12115/121150D/Advanced-high-fidelity-autonomy-systems-simulation/10.1117/12.2618011.full},
	doi = {10.1117/12.2618011},
	abstract = {The United State Army Corp of Engineers (USACE) Engineering Research and Development Center (ERDC) has developed a suite of computational tools called the Computational Test Bed (CTB) for advanced high-fidelity physics-based autonomous vehicle sensor and environment simulations. These tools provide insights into onboard navigation, image processing, sensor fusion techniques, and rapid data generation for artificial intelligence and machine learning techniques across the full spectrum (visible, NIR, MWIR, and LWIR) and for various sensor modalities (LiDAR, EO, radar). This paper presents ERDC’s CTB that allows the community to design, develop, test, and evaluate the entire autonomy space from machine learning algorithm development using augmented synthetic data to large-scale autonomous system testing.},
	urldate = {2024-06-20},
	booktitle = {Autonomous {Systems}: {Sensors}, {Processing} and {Security} for {Ground}, {Air}, {Sea} and {Space} {Vehicles} and {Infrastructure} 2022},
	publisher = {SPIE},
	author = {Carrillo, Justin T. and Cecil, Orie M. and Monroe, John G. and Trautz, Andrew C. and Farthing, Matthew W. and Bray, Matthew D.},
	month = jun,
	year = {2022},
	pages = {109--115},
}

The United State Army Corp of Engineers (USACE) Engineering Research and Development Center (ERDC) has developed a suite of computational tools called the Computational Test Bed (CTB) for advanced high-fidelity physics-based autonomous vehicle sensor and environment simulations. These tools provide insights into onboard navigation, image processing, sensor fusion techniques, and rapid data generation for artificial intelligence and machine learning techniques across the full spectrum (visible, NIR, MWIR, and LWIR) and for various sensor modalities (LiDAR, EO, radar). This paper presents ERDC’s CTB that allows the community to design, develop, test, and evaluate the entire autonomy space from machine learning algorithm development using augmented synthetic data to large-scale autonomous system testing.

@inproceedings{mcdougal_single-antenna_2022,
	title = {Single-{Antenna} {Low} {Earth} {Orbit} {Signal} {Simulator} for {Hardware} in the {Loop} {Testing}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=18383},
	doi = {10.33012/2022.18383},
	abstract = {Simulation tools are vital to the engineering design process. They allow for changes and modifications to current test plans before production or implementation. With regard to global navigation satellite systems (GNSSs), such as the global positioning system (GPS), signal simulation tools help with the design of software defined receivers and allow for testing of error mitigation. With recent research featuring navigation with signals of opportunity and low Earth orbit (LEO) satellite constellations, a signal simulation tool is applicable here as well. In this paper a signal simulation tool for LEO satellite navigation is developed. This simulation tool is block-like to provide flexibility to the user which allows for fast testing of various signal types and constellations. The simulation in this paper focuses on two LEO constellations, Iridium and Orbcomm. To demonstrate the simulation tool, a navigation signal is designed for both constellations. Then, the broadcast of this signal is simulated. A receiver is designed to process the simulated signal, and a navigation solution is computed. This simulation tool shows effectiveness at simulating multiple LEO constellations and generates realistic signals that receivers can process.},
	language = {en},
	urldate = {2024-06-20},
	author = {McDougal, Samuel and Morgan, Samuel and Martin, Scott},
	month = sep,
	year = {2022},
	pages = {2349--2361},
}

Simulation tools are vital to the engineering design process. They allow for changes and modifications to current test plans before production or implementation. With regard to global navigation satellite systems (GNSSs), such as the global positioning system (GPS), signal simulation tools help with the design of software defined receivers and allow for testing of error mitigation. With recent research featuring navigation with signals of opportunity and low Earth orbit (LEO) satellite constellations, a signal simulation tool is applicable here as well. In this paper a signal simulation tool for LEO satellite navigation is developed. This simulation tool is block-like to provide flexibility to the user which allows for fast testing of various signal types and constellations. The simulation in this paper focuses on two LEO constellations, Iridium and Orbcomm. To demonstrate the simulation tool, a navigation signal is designed for both constellations. Then, the broadcast of this signal is simulated. A receiver is designed to process the simulated signal, and a navigation solution is computed. This simulation tool shows effectiveness at simulating multiple LEO constellations and generates realistic signals that receivers can process.

@inproceedings{smith_detection_2022,
	title = {Detection and {Localization} of {GPS} {Interference} {Source} {Based} on {Clock} {Signatures}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=18450},
	doi = {10.33012/2022.18450},
	abstract = {This paper focuses on the development and testing of spoofing detection and localization techniques that rely only on clock deviations to identify threat signals. Detection methods that rely on dynamic receiver geometries to triangulate threat locations or signal geometry to identify spoofing are not considered here. Instead, this paper focuses on single antenna receivers and assumes the receiver tracks only the inauthentic signal. The quality of the receiver clock has a significant impact on the performance of the receiver tracking loops. Low quality clocks have frequency instabilities that inherently limit the sensitivity of the receiver to slow growing errors. Some clocks provide better frequency stabilities but have a higher white frequency noise that can induce false detections. Because of these trends, various detection methods are tested with four types of receiver and transmitter clocks of varying quality.},
	language = {en},
	urldate = {2024-06-20},
	author = {Smith, Joseph B. and Wood, Joshua M. and Martin, Scott M. and Brashar, Connor},
	month = sep,
	year = {2022},
	pages = {3528--3540},
}

This paper focuses on the development and testing of spoofing detection and localization techniques that rely only on clock deviations to identify threat signals. Detection methods that rely on dynamic receiver geometries to triangulate threat locations or signal geometry to identify spoofing are not considered here. Instead, this paper focuses on single antenna receivers and assumes the receiver tracks only the inauthentic signal. The quality of the receiver clock has a significant impact on the performance of the receiver tracking loops. Low quality clocks have frequency instabilities that inherently limit the sensitivity of the receiver to slow growing errors. Some clocks provide better frequency stabilities but have a higher white frequency noise that can induce false detections. Because of these trends, various detection methods are tested with four types of receiver and transmitter clocks of varying quality.

@unpublished{strong_utilizing_2021,
	title = {Utilizing {Hidden} {Markov} {Models} to {Classify} {Maneuvers} and {Improve} {Estimates} of an {Unmanned} {Aerial} {Vehicle} {During} {High} {Dynamic} {Flight}},
	url = {https://etd.auburn.edu//handle/10415/7886},
	abstract = {Unmanned Aerial Vehicles (UAVs) are an increasing presence around the world; however, they can pose a threat to secure facilities. Many UAV mitigation techniques require accurate knowledge of UAV states to successfully intercept an adversarial UAV, but access to UAV on-board sensors may not be possible. One potential solution to this problem is to estimate UAV states using only radar measurements. This scenario is examined in simulation and with real world data. A discrete Extended Kalman Filter (EKF) with a constant acceleration dynamic model provides a baseline estimation performance of simulated UAV maneuvers and is shown to have consistent error in state estimates during high dynamic maneuvers. The simulated UAV maneuvers are then modelled as Hidden Markov Models (HMMs). HMMs are utilized to perform real time classification of maneuvers and to provide acceleration and jerk estimates of the UAV through the use of a Gaussian Mixture Regression. HMM classification of simulated maneuvers results in high accuracy classification during UAV flight. The HMM acceleration and jerk estimates are then incorporated into a state estimation framework as inputs to the filter’s dynamic model. This new system is known as the EKF+HMM. When estimating high dynamic maneuvers, the EKF+HMM performs better than the baseline EKF, while performing at similar levels when estimating low dynamic maneuvers. HMM classification and the EKF+HMM are also tested on a real world data set of maneuvers performed by a Tarot X8 Octacopter. HMMs were trained for each maneuver, using experimental data or simulated data. HMM classification was successful using both types of HMMs, although models trained with experimental data performed better. The EKF+HMM was also tested on the real-world data set and performed worse than the EKF when using simulation data trained HMMs and at the same level as the EKF when using HMMs trained with experimental data.},
	language = {en},
	urldate = {2024-06-25},
	author = {Strong, Amy},
	month = jul,
	year = {2021},
	note = {Accepted: 2021-07-28T19:09:59Z},
}

Unmanned Aerial Vehicles (UAVs) are an increasing presence around the world; however, they can pose a threat to secure facilities. Many UAV mitigation techniques require accurate knowledge of UAV states to successfully intercept an adversarial UAV, but access to UAV on-board sensors may not be possible. One potential solution to this problem is to estimate UAV states using only radar measurements. This scenario is examined in simulation and with real world data. A discrete Extended Kalman Filter (EKF) with a constant acceleration dynamic model provides a baseline estimation performance of simulated UAV maneuvers and is shown to have consistent error in state estimates during high dynamic maneuvers. The simulated UAV maneuvers are then modelled as Hidden Markov Models (HMMs). HMMs are utilized to perform real time classification of maneuvers and to provide acceleration and jerk estimates of the UAV through the use of a Gaussian Mixture Regression. HMM classification of simulated maneuvers results in high accuracy classification during UAV flight. The HMM acceleration and jerk estimates are then incorporated into a state estimation framework as inputs to the filter’s dynamic model. This new system is known as the EKF+HMM. When estimating high dynamic maneuvers, the EKF+HMM performs better than the baseline EKF, while performing at similar levels when estimating low dynamic maneuvers. HMM classification and the EKF+HMM are also tested on a real world data set of maneuvers performed by a Tarot X8 Octacopter. HMMs were trained for each maneuver, using experimental data or simulated data. HMM classification was successful using both types of HMMs, although models trained with experimental data performed better. The EKF+HMM was also tested on the real-world data set and performed worse than the EKF when using simulation data trained HMMs and at the same level as the EKF when using HMMs trained with experimental data.

@unpublished{pryor_evaluation_2021,
	title = {Evaluation of {Cooperative} {Navigation} {Strategies} with {Maneuvering} {UAVs}},
	url = {https://etd.auburn.edu//handle/10415/7871},
	abstract = {This thesis presents and evaluates cooperative navigation methods used to reduce navigation solution error growth between members of an unmanned aerial vehicle - unmanned ground vehicle (UAV-UGV) or all-UAV team when Global Position System (GPS) measurements are partially or completely unavailable to the group. Multiple scenarios with varying numbers of vehicles were simulated with a centralized navigation algorithm based on the Extended Kalman Filter (EKF) and with a decentralized navigation algorithm based on the Covariance Intersection (CI) filter. Measurements including relative range, relative range-rate, and relative bearing were made available to the vehicles in different simulation runs to compare their impact on navigation state observability and navigation state estimation accuracy. The UAVs were also guided along varied trajectories of a ``spiral" class during different simulation runs to investigate whether estimation accuracy can be improved by varying inter-vehicle dynamics and geometry.

The results of these studies show that cooperative navigation is a promising strategy to reduce navigation state error growth. To analyze the observability of the studied scenarios, a condition number test was performed on the observability Gramian matrix. This study indicates that the navigation state observability in cooperative navigation scenarios where a kinematic vehicle model is aided with relative measurements can be improved by the proposed vehicle maneuver. As the rate of the proposed spiral maneuver is increased, this analysis suggests an improvement in observability. This result is further validated in the simulated results which show that with relative bearing only, even low rates of inter-vehicle spiral motion allow for estimates of relative position with less than 3 meters of error. As the spiral rate increases, accurate relative positioning is shown to be possible with only relative range measurements. IMU biases are also shown to be estimated for cooperative groups with low meter-level relative positioning error but no absolute position reference. In scenarios where the vehicles can accurately estimate their relative positions and at least one vehicle in the cooperative group has access to accurate GPS information, all of the vehicles in the cooperative group benefit equally through communication with that vehicle. In UAV-UGV scenarios, the cooperative group includes a heterogeneous mixture of vehicles equipped with high and low quality inertial navigation systems (INS) and/or alternative navigation methods. In this case, if the vehicles can estimate their relative positions to meter-level accuracy, all cooperating vehicles benefit with navigation solution error characteristics matching that of the most accurate navigation system in the group.

Lastly, experimentally collected data was analyzed to validate the simulation results. This experiment demonstrated similar results to the simulated scenarios. Relative position error was reduced from over 100 meters to sub-meter accuracy, depending on relative measurement availability. Absolute error was also reduced from over 70 meters (in the IMU-only case) to meter-level accuracy depending on measurement availability.},
	language = {en},
	urldate = {2024-06-25},
	author = {Pryor, Jacob},
	month = jul,
	year = {2021},
	note = {Accepted: 2021-07-27T14:46:13Z},
}

This thesis presents and evaluates cooperative navigation methods used to reduce navigation solution error growth between members of an unmanned aerial vehicle - unmanned ground vehicle (UAV-UGV) or all-UAV team when Global Position System (GPS) measurements are partially or completely unavailable to the group. Multiple scenarios with varying numbers of vehicles were simulated with a centralized navigation algorithm based on the Extended Kalman Filter (EKF) and with a decentralized navigation algorithm based on the Covariance Intersection (CI) filter. Measurements including relative range, relative range-rate, and relative bearing were made available to the vehicles in different simulation runs to compare their impact on navigation state observability and navigation state estimation accuracy. The UAVs were also guided along varied trajectories of a ``spiral" class during different simulation runs to investigate whether estimation accuracy can be improved by varying inter-vehicle dynamics and geometry. The results of these studies show that cooperative navigation is a promising strategy to reduce navigation state error growth. To analyze the observability of the studied scenarios, a condition number test was performed on the observability Gramian matrix. This study indicates that the navigation state observability in cooperative navigation scenarios where a kinematic vehicle model is aided with relative measurements can be improved by the proposed vehicle maneuver. As the rate of the proposed spiral maneuver is increased, this analysis suggests an improvement in observability. This result is further validated in the simulated results which show that with relative bearing only, even low rates of inter-vehicle spiral motion allow for estimates of relative position with less than 3 meters of error. As the spiral rate increases, accurate relative positioning is shown to be possible with only relative range measurements. IMU biases are also shown to be estimated for cooperative groups with low meter-level relative positioning error but no absolute position reference. In scenarios where the vehicles can accurately estimate their relative positions and at least one vehicle in the cooperative group has access to accurate GPS information, all of the vehicles in the cooperative group benefit equally through communication with that vehicle. In UAV-UGV scenarios, the cooperative group includes a heterogeneous mixture of vehicles equipped with high and low quality inertial navigation systems (INS) and/or alternative navigation methods. In this case, if the vehicles can estimate their relative positions to meter-level accuracy, all cooperating vehicles benefit with navigation solution error characteristics matching that of the most accurate navigation system in the group. Lastly, experimentally collected data was analyzed to validate the simulation results. This experiment demonstrated similar results to the simulated scenarios. Relative position error was reduced from over 100 meters to sub-meter accuracy, depending on relative measurement availability. Absolute error was also reduced from over 70 meters (in the IMU-only case) to meter-level accuracy depending on measurement availability.

@unpublished{meyer_online_2021,
	title = {Online {Rotational} {Self}-{Calibration} of {LiDAR} {Sensors} when {Mounted} on a {Ground} {Vehicle}},
	url = {https://etd.auburn.edu//handle/10415/7938},
	abstract = {This thesis presents a method for online extrinsic rotational calibration of a LiDAR sensor 
with minimal manual intervention. The approach leverages the expected geometry of structured 
environments common to ground vehicle applications to correct for sensor-to-vehicle rotational 
misalignment without the need of calibration targets, additional sensors, or an accurate model of 
vehicle kinematics or dynamics. Once an extrinsic calibration transform is estimated by this 
approach, it can be applied to the raw LiDAR data to transform it into a frame with known relation 
to other calibrated sensors and points of interest on the vehicle body, such as a control point or 
vehicle frame origin. This approach may be used in applications that involve the vehicle following 
the trajectory of a distinct, straight section of a road or pathway, and where the sensor collection 
initiated with the vehicle at rest on an extended level surface. To estimate the yaw offset, the road 
trajectory is detected, and for the roll and pitch offsets, the orientation of the ground plane in front 
of the vehicle is estimated. This thesis also proposes a novel road edge and lane line marking 
detection algorithm capable of detecting the edges and markings at arbitrary orientations and 
locations as required for estimating the LiDAR yaw offset, as well as details an approach for 
estimating the ground orientations. The approach estimates roll and pitch offsets up to 90 degrees, 
and yaw offsets of up to 45 degrees with respect to a level LiDAR with x-axis aligned with the 
forward x-axis of the vehicle it is mounted to. In testing, the estimated calibration was able to 
correct for dynamic roll and pitch estimations of the ground plane to a root mean square error of 
within 1.20 and 2.11 degrees in roll and pitch respectively over all tested scenarios, and was within 
0.099 and 0.119 degrees in roll and pitch when the ground orientation remained constant with 
respect to gravity. The road edge orientation detection was able to detect road lines in 80\% of 
tested frames with a root mean square error of 0.47 degrees in detected line orientation.},
	language = {en},
	urldate = {2024-06-25},
	author = {Meyer, Stephanie},
	month = aug,
	year = {2021},
	note = {Accepted: 2021-08-06T16:05:02Z},
}

This thesis presents a method for online extrinsic rotational calibration of a LiDAR sensor with minimal manual intervention. The approach leverages the expected geometry of structured environments common to ground vehicle applications to correct for sensor-to-vehicle rotational misalignment without the need of calibration targets, additional sensors, or an accurate model of vehicle kinematics or dynamics. Once an extrinsic calibration transform is estimated by this approach, it can be applied to the raw LiDAR data to transform it into a frame with known relation to other calibrated sensors and points of interest on the vehicle body, such as a control point or vehicle frame origin. This approach may be used in applications that involve the vehicle following the trajectory of a distinct, straight section of a road or pathway, and where the sensor collection initiated with the vehicle at rest on an extended level surface. To estimate the yaw offset, the road trajectory is detected, and for the roll and pitch offsets, the orientation of the ground plane in front of the vehicle is estimated. This thesis also proposes a novel road edge and lane line marking detection algorithm capable of detecting the edges and markings at arbitrary orientations and locations as required for estimating the LiDAR yaw offset, as well as details an approach for estimating the ground orientations. The approach estimates roll and pitch offsets up to 90 degrees, and yaw offsets of up to 45 degrees with respect to a level LiDAR with x-axis aligned with the forward x-axis of the vehicle it is mounted to. In testing, the estimated calibration was able to correct for dynamic roll and pitch estimations of the ground plane to a root mean square error of within 1.20 and 2.11 degrees in roll and pitch respectively over all tested scenarios, and was within 0.099 and 0.119 degrees in roll and pitch when the ground orientation remained constant with respect to gravity. The road edge orientation detection was able to detect road lines in 80% of tested frames with a root mean square error of 0.47 degrees in detected line orientation.

@unpublished{kamrath_ambiguous_2021,
	title = {Ambiguous {Energy} {Suppression} in {Encryption} {Derived} {Pseudo}-{Random} {BPSK} {Radar} {Signals}},
	url = {https://etd.auburn.edu//handle/10415/8008},
	abstract = {In this thesis, a pseudo-random binary phase shift keying (BPSK) radar signal is developed using Advanced Encryption Standard (AES-192). The primary objective of this encryption based BPSK (E-BPSK) signal is to provide a fast user controlled means of generating a secure a-periodic radar signal which presents several desirable characteristics. These include virtually no ambiguous range interval, high noise tolerance and spoofing security through unpredictability. Statistical analysis of a simulated data model of the E-BPSK signal is performed to verify the randomness of the encryption based sequence. A comparison signal of identical transmit properties with a different modulation code is used for a detailed comparative analysis. The standard matched filter response of E-BPSK has a sharp main lobe peak at a real target location. The random nature of the signal due to the encryption also causes a significant amount of ambiguous side-lobe energy in both the range and Doppler axis of the matched filter. A method of suppressing this side-lobe ambiguous energy is required to enable multi-target identification. This thesis covers mitigating the ambiguous energy in the proposed E-BPSK signal with a modified CLEAN type algorithm specifically designed for an a-periodic signal. CLEAN involves identifying targets and reprocessing the signal after extracting the identified target energy. CLEAN algorithms can become hardware intensive and are sensitive to the target model accuracy. Fitness functions for optimizing the CLEAN target model parameters are included to increase model accuracy. In simulation the modified CLEAN algorithm successfully reduces the ambiguous side-lobe energy in the E-BPSK matched filter response by up to -30 dB. CLEAN processing applied to a discrete random signal is shown to effectively mitigate the ambiguous lobes in the matched filter while preserving the range and Doppler ambiguity mitigation characteristics.},
	language = {en},
	urldate = {2024-06-25},
	author = {Kamrath, Luke},
	month = dec,
	year = {2021},
	note = {Accepted: 2021-12-01T15:02:57Z},
}

In this thesis, a pseudo-random binary phase shift keying (BPSK) radar signal is developed using Advanced Encryption Standard (AES-192). The primary objective of this encryption based BPSK (E-BPSK) signal is to provide a fast user controlled means of generating a secure a-periodic radar signal which presents several desirable characteristics. These include virtually no ambiguous range interval, high noise tolerance and spoofing security through unpredictability. Statistical analysis of a simulated data model of the E-BPSK signal is performed to verify the randomness of the encryption based sequence. A comparison signal of identical transmit properties with a different modulation code is used for a detailed comparative analysis. The standard matched filter response of E-BPSK has a sharp main lobe peak at a real target location. The random nature of the signal due to the encryption also causes a significant amount of ambiguous side-lobe energy in both the range and Doppler axis of the matched filter. A method of suppressing this side-lobe ambiguous energy is required to enable multi-target identification. This thesis covers mitigating the ambiguous energy in the proposed E-BPSK signal with a modified CLEAN type algorithm specifically designed for an a-periodic signal. CLEAN involves identifying targets and reprocessing the signal after extracting the identified target energy. CLEAN algorithms can become hardware intensive and are sensitive to the target model accuracy. Fitness functions for optimizing the CLEAN target model parameters are included to increase model accuracy. In simulation the modified CLEAN algorithm successfully reduces the ambiguous side-lobe energy in the E-BPSK matched filter response by up to -30 dB. CLEAN processing applied to a discrete random signal is shown to effectively mitigate the ambiguous lobes in the matched filter while preserving the range and Doppler ambiguity mitigation characteristics.

@unpublished{givhan_gps_2021,
	title = {A {GPS} {L5} {Software} {Defined} {Vector} {Tracking} {Receiver}},
	url = {https://etd.auburn.edu//handle/10415/7943},
	abstract = {As the world continues towards autonomy, the need for continuous, precise, and robust navigation is becoming increasingly important. A new wave of modernized Global Navigation Satellite Systems (GNSS) signals are currently being implemented on the latest satellite blocks. The focus of this work is on the Global Positioning System (GPS) L5 signal, and while it is not yet fully available there are now windows of time where experimental data can be used to test modified algorithms exploiting the nature of the new signal structures. The GPS L5 signal is a Quadrature Phase-Shift keying (QPSK) signal that has both an in-phase (data) and quadrature (pilot) arm in the signal that are transmitted together. The pilot channel is not modulated with a data message which historically limits the length of coherent integration during tracking. This work adapts a vector tracking algorithm, which has been shown in prior works to provide a more robust navigation solution than scalar tracking architectures, to the GPS L5 signal structure. The traditional vector tracking architecture for both GPS L1 and L5 quadrature independently are compared to adapted methods. For the first method, the L5 in-phase and L5 quadrature discriminator measurements are combined before being added to the Kalman filter to update the Position, Velocity, and Timing (PVT) solution and Numerically Controlled Oscillators (NCOs). For the second method, L5 in-phase and L5 quadrature are tracked independently and both provide measurements to the same filter for PVT and NCO updates. This second method removes the limit on integration lengths for the L5 quadrature channel allowing for varying extended integration lengths on this channel. All methods are post processed on live sky data from only Block IIF and III satellites and simulated data from a Spirent GNSS simulator and evaluated. A covariance analysis is also performed comparing the methods. Lastly an ionospheric free vector tracking measurement is developed and applied to a GPS L1 GPS L5 dual frequency vector tracking receiver. This receivers results are compared against a single frequency receiver with an ionospheric model for corrections. The GPS L5 receiver with extended integration periods provided an improvement to the stability of the receiver in degraded environments and provided better filtering of measurements and states. The GPS L5 combined receiver was able to increase the tracking threshold of the receiver by 1-3 dB-Hz over receivers with equivalent integration periods. The ionospheric free combination receiver was able to provide equivalent results to the ionospheric model in simulation, but the live sky results were not as stable as the simulated results. The linear combination of the two vector tracking measurements greatly increases the variance of the measurements.},
	language = {en},
	urldate = {2024-06-25},
	author = {Givhan, Charles Anderson},
	month = aug,
	year = {2021},
	note = {Accepted: 2021-08-11T20:09:38Z},
}

As the world continues towards autonomy, the need for continuous, precise, and robust navigation is becoming increasingly important. A new wave of modernized Global Navigation Satellite Systems (GNSS) signals are currently being implemented on the latest satellite blocks. The focus of this work is on the Global Positioning System (GPS) L5 signal, and while it is not yet fully available there are now windows of time where experimental data can be used to test modified algorithms exploiting the nature of the new signal structures. The GPS L5 signal is a Quadrature Phase-Shift keying (QPSK) signal that has both an in-phase (data) and quadrature (pilot) arm in the signal that are transmitted together. The pilot channel is not modulated with a data message which historically limits the length of coherent integration during tracking. This work adapts a vector tracking algorithm, which has been shown in prior works to provide a more robust navigation solution than scalar tracking architectures, to the GPS L5 signal structure. The traditional vector tracking architecture for both GPS L1 and L5 quadrature independently are compared to adapted methods. For the first method, the L5 in-phase and L5 quadrature discriminator measurements are combined before being added to the Kalman filter to update the Position, Velocity, and Timing (PVT) solution and Numerically Controlled Oscillators (NCOs). For the second method, L5 in-phase and L5 quadrature are tracked independently and both provide measurements to the same filter for PVT and NCO updates. This second method removes the limit on integration lengths for the L5 quadrature channel allowing for varying extended integration lengths on this channel. All methods are post processed on live sky data from only Block IIF and III satellites and simulated data from a Spirent GNSS simulator and evaluated. A covariance analysis is also performed comparing the methods. Lastly an ionospheric free vector tracking measurement is developed and applied to a GPS L1 GPS L5 dual frequency vector tracking receiver. This receivers results are compared against a single frequency receiver with an ionospheric model for corrections. The GPS L5 receiver with extended integration periods provided an improvement to the stability of the receiver in degraded environments and provided better filtering of measurements and states. The GPS L5 combined receiver was able to increase the tracking threshold of the receiver by 1-3 dB-Hz over receivers with equivalent integration periods. The ionospheric free combination receiver was able to provide equivalent results to the ionospheric model in simulation, but the live sky results were not as stable as the simulated results. The linear combination of the two vector tracking measurements greatly increases the variance of the measurements.

@unpublished{castleberry_methods_2021,
	title = {Methods for {Improving} {Visual} {Terrain} {Relative} {Navigation} for {Dynamic} {Aerial} {Systems}},
	url = {https://etd.auburn.edu//handle/10415/7699},
	abstract = {One popular means of aerial localization and navigation in GPS-denied environments is visual terrain relative navigation.  Terrain relative navigation involves performing image registration with sensed aerial camera imagery and georeferenced satellite maps to produce the geographic translation and rotation of the camera.  One popular terrain relative navigation technique depends on matching feature descriptors.  These features, however, are intolerant to major changes in perspective, light, vegetation, season, and other scene changes and produce excessive amounts of false matches.  Alternatively, image correlation can be used for registering a sensed image to a reference image but is extremely intolerant to perspective differences for 6 degree of freedom camera systems.
This research explores the use of a combination of corner detection and normalized cross correlation for aerial vehicles at different altitudes.  New methods for using dynamic search windows within reference satellite imagery are explored to constrain the pose estimation and increase image matching accuracy.  The algorithm is tested with both simulated aerial imagery and experimentally sensed imagery captured with rigid mounted cameras on unmanned aerial vehicles and high altitude balloons.  It is evaluated on its successful match rate and pose estimation error compared to GPS.   It has approximately 75\% successful match rate in simulation and 20\% successful match rate in experimental datasets.  The filtered pose estimate error is decreased in simulation in effectively over 95\% of the frames and 20\% in the experimental cases.  Integration of this algorithm with other navigational sensors and algorithms would provide improvements to the overall navigation solution.},
	language = {en},
	urldate = {2024-06-25},
	author = {Castleberry, Matthew},
	month = apr,
	year = {2021},
	note = {Accepted: 2021-04-26T13:30:13Z},
}

One popular means of aerial localization and navigation in GPS-denied environments is visual terrain relative navigation. Terrain relative navigation involves performing image registration with sensed aerial camera imagery and georeferenced satellite maps to produce the geographic translation and rotation of the camera. One popular terrain relative navigation technique depends on matching feature descriptors. These features, however, are intolerant to major changes in perspective, light, vegetation, season, and other scene changes and produce excessive amounts of false matches. Alternatively, image correlation can be used for registering a sensed image to a reference image but is extremely intolerant to perspective differences for 6 degree of freedom camera systems. This research explores the use of a combination of corner detection and normalized cross correlation for aerial vehicles at different altitudes. New methods for using dynamic search windows within reference satellite imagery are explored to constrain the pose estimation and increase image matching accuracy. The algorithm is tested with both simulated aerial imagery and experimentally sensed imagery captured with rigid mounted cameras on unmanned aerial vehicles and high altitude balloons. It is evaluated on its successful match rate and pose estimation error compared to GPS. It has approximately 75% successful match rate in simulation and 20% successful match rate in experimental datasets. The filtered pose estimate error is decreased in simulation in effectively over 95% of the frames and 20% in the experimental cases. Integration of this algorithm with other navigational sensors and algorithms would provide improvements to the overall navigation solution.

@unpublished{wood_detection_2021,
	title = {Detection of {GNSS} {Faults} {Using} {Receiver} {Clock} {Drift} {Estimates}},
	url = {https://etd.auburn.edu//handle/10415/7749},
	abstract = {GNSS based navigation systems are used in almost every sector, from industrial and agricultural environments to everyday applications such as personal navigation or autonomous vehicles. Satellite navigation provides accurate position estimates for these applications, however the performance can be interrupted or degraded by intentional or unintentional interference from inauthentic transmitters. These transmitters can range from GNSS repeaters used for indoor or underground navigation to individuals attempting to fool cellular games into believing they are in another location. This thesis develops a GNSS interference detection method for moving platforms using clock drift estimate monitoring by combining GNSS measurements with inertial navigation systems. During normal operation, GNSS satellites have negligible clock drift, allowing the receiver to estimate the drift of the local oscillator present in the user hardware. When additional transmitters using unsynchronized or low quality oscillators transmit counterfeit GNSS signals, the estimated clock drift will reflect not only the receiver clock drift but also the drift of the transmitter clock. Prior work has demonstrated that estimates of receiver clock drift provide a viable option for integrity monitoring at a static location, however the assumptions shown do not hold for dynamic platforms. By incorporating additional sensors into the algorithm, the clock drift can be estimated for dynamic platforms such as autonomous vehicles or commercial drones. The proposed clock drift monitoring algorithm is analyzed using various quality receiver clocks and inertial sensors, expanding the capabilities beyond that of a standard GNSS receiver. The developed algorithm utilizes time-differenced carrier phase measurements and mechanized INS measurements to provide estimates of the receiver clock drift prior to using the measurements to update the navigation solution, allowing for the detection of measurement faults before the faults influence the state estimate. Two methods of GNSS/INS coupling are compared, which are used to provide position estimates for use in the clock drift estimation algorithm.},
	language = {en},
	urldate = {2024-06-25},
	author = {Wood, Joshua},
	month = may,
	year = {2021},
	note = {Accepted: 2021-05-25T20:38:25Z},
}

GNSS based navigation systems are used in almost every sector, from industrial and agricultural environments to everyday applications such as personal navigation or autonomous vehicles. Satellite navigation provides accurate position estimates for these applications, however the performance can be interrupted or degraded by intentional or unintentional interference from inauthentic transmitters. These transmitters can range from GNSS repeaters used for indoor or underground navigation to individuals attempting to fool cellular games into believing they are in another location. This thesis develops a GNSS interference detection method for moving platforms using clock drift estimate monitoring by combining GNSS measurements with inertial navigation systems. During normal operation, GNSS satellites have negligible clock drift, allowing the receiver to estimate the drift of the local oscillator present in the user hardware. When additional transmitters using unsynchronized or low quality oscillators transmit counterfeit GNSS signals, the estimated clock drift will reflect not only the receiver clock drift but also the drift of the transmitter clock. Prior work has demonstrated that estimates of receiver clock drift provide a viable option for integrity monitoring at a static location, however the assumptions shown do not hold for dynamic platforms. By incorporating additional sensors into the algorithm, the clock drift can be estimated for dynamic platforms such as autonomous vehicles or commercial drones. The proposed clock drift monitoring algorithm is analyzed using various quality receiver clocks and inertial sensors, expanding the capabilities beyond that of a standard GNSS receiver. The developed algorithm utilizes time-differenced carrier phase measurements and mechanized INS measurements to provide estimates of the receiver clock drift prior to using the measurements to update the navigation solution, allowing for the detection of measurement faults before the faults influence the state estimate. Two methods of GNSS/INS coupling are compared, which are used to provide position estimates for use in the clock drift estimation algorithm.

@inproceedings{siefert_using_2021,
	title = {Using {Demanded} {Power} and {RDE} {Aggressiveness} {Metrics} to {Analyze} the {Impact} of {CACC} {Aggressiveness} on {Heavy} {Duty} {Platooning} {Power} {Consumption}},
	volume = {2021},
	url = {https://www.osti.gov/biblio/1833573},
	doi = {10.4271/2021-01-0069},
	abstract = {Presently, a main mobility sector objective is to reduce its impact on the global greenhouse gas emissions. While there are many techniques being explored, a promising approach to improve fuel economy is to reduce the required energy by using slipstream effects. This study analyzes the demanded engine power and mechanical energy used by heavy-duty trucks during platooning and non-platooning operation to determine the aerodynamic benefits of the slipstream. A series of platooning tests utilizing class 8 semi-trucks platooning via Cooperative Adaptive Cruise Control (CACC) are performed. Comparing the demanded engine power and mechanical energy used reveals the benefits of platooning on the aerodynamic drag while disregarding any potential negative side effects on the engine. However, energy savings were lower than expected in some cases. It was hypothesized that the CACC may have amplified transient platooning events relative to the individual truck baseline results, hampering the potential energy savings. Therefore, the impact of the controller on the observed driving style was analyzed in detail. In order to quantify the transient operational characteristics of the experimental trials, metrics from the European Real Driving Emissions (RDE) legislation were modified to serve as metrics of aggressiveness during platooning. The metrics (v · apos)95 and Relative Positive Acceleration (RPA) were calculated for platooning and non-platooning runs. These results indicate that the CACC induces small acceleration events during platooning to retain the commanded longitudinal separation between vehicles. These small acceleration events increase following vehicle aggressiveness during platooning and prevent the following vehicles from obtaining maximum energy savings. Moreover, a correlation between the RDE metric (v · apos)95 and energy savings is developed. Hence, this work establishes the ability of RDE metrics to assess CACC impacts on platoon energy savings.},
	language = {English},
	urldate = {2024-06-20},
	booktitle = {{SAE} {Technical} {Paper} {Series}},
	author = {Siefert, Jan and Stegner, Evan and Snitzer, Philip and Ward, Jacob and Bevly, David M. and Hoffman, Mark and Kotz, Andrew},
	month = apr,
	year = {2021},
}

Presently, a main mobility sector objective is to reduce its impact on the global greenhouse gas emissions. While there are many techniques being explored, a promising approach to improve fuel economy is to reduce the required energy by using slipstream effects. This study analyzes the demanded engine power and mechanical energy used by heavy-duty trucks during platooning and non-platooning operation to determine the aerodynamic benefits of the slipstream. A series of platooning tests utilizing class 8 semi-trucks platooning via Cooperative Adaptive Cruise Control (CACC) are performed. Comparing the demanded engine power and mechanical energy used reveals the benefits of platooning on the aerodynamic drag while disregarding any potential negative side effects on the engine. However, energy savings were lower than expected in some cases. It was hypothesized that the CACC may have amplified transient platooning events relative to the individual truck baseline results, hampering the potential energy savings. Therefore, the impact of the controller on the observed driving style was analyzed in detail. In order to quantify the transient operational characteristics of the experimental trials, metrics from the European Real Driving Emissions (RDE) legislation were modified to serve as metrics of aggressiveness during platooning. The metrics (v · apos)95 and Relative Positive Acceleration (RPA) were calculated for platooning and non-platooning runs. These results indicate that the CACC induces small acceleration events during platooning to retain the commanded longitudinal separation between vehicles. These small acceleration events increase following vehicle aggressiveness during platooning and prevent the following vehicles from obtaining maximum energy savings. Moreover, a correlation between the RDE metric (v · apos)95 and energy savings is developed. Hence, this work establishes the ability of RDE metrics to assess CACC impacts on platoon energy savings.

@inproceedings{meyer_automatic_2021,
	series = {Modeling, {Estimation} and {Control} {Conference} {MECC} 2021},
	title = {Automatic {Extrinsic} {Rotational} {Calibration} of {LiDAR} {Sensors} and {Vehicle} {Orientation} {Estimation}},
	volume = {54},
	url = {https://www.sciencedirect.com/science/article/pii/S2405896321022540},
	doi = {10.1016/j.ifacol.2021.11.210},
	abstract = {Whether a vehicle is being used for an autonomous mission or in support of data collection and research, extrinsic calibration to align the vehicle’s sensors to a reference point on the vehicle is integral to ensuring that quality data is available to the system. This is particularly true for vision and distance sensors, such as LiDAR, which must be well-located with respect to the vehicle body before they can provide meaningful localization or environmental modeling assistance. This paper outlines an automatic approach for calibrating a LiDAR to the body of a ground vehicle using only the data from the LiDAR itself. This approach assumes that the LiDAR is able to sample at least a one meter square section of level ground, and that the vehicle travels along a straight section of roadway with a well-marked road edge at some point during the calibration, while closely following the trajectory of the road edge. This method has been able to automatically calibrate a LiDAR to yield 0.08 and 0.12 degrees of error in roll and pitch respectively when comparing estimated ground pitch and roll to the orientation estimates from a truth sensor.},
	urldate = {2024-06-20},
	booktitle = {{IFAC}-{PapersOnLine}},
	author = {Meyer, Stephanie W. and Chen, Howard and Bevly, David M.},
	month = jan,
	year = {2021},
	keywords = {Autonomous Mobile Robots, Autonomous Vehicles, Sensing, Sensor calibration, Sensor integration, perception},
	pages = {424--429},
}

Whether a vehicle is being used for an autonomous mission or in support of data collection and research, extrinsic calibration to align the vehicle’s sensors to a reference point on the vehicle is integral to ensuring that quality data is available to the system. This is particularly true for vision and distance sensors, such as LiDAR, which must be well-located with respect to the vehicle body before they can provide meaningful localization or environmental modeling assistance. This paper outlines an automatic approach for calibrating a LiDAR to the body of a ground vehicle using only the data from the LiDAR itself. This approach assumes that the LiDAR is able to sample at least a one meter square section of level ground, and that the vehicle travels along a straight section of roadway with a well-marked road edge at some point during the calibration, while closely following the trajectory of the road edge. This method has been able to automatically calibrate a LiDAR to yield 0.08 and 0.12 degrees of error in roll and pitch respectively when comparing estimated ground pitch and roll to the orientation estimates from a truth sensor.

@inproceedings{stegner_experimental_2021,
	address = {Warrendale, PA},
	title = {Experimental {Fuel} {Consumption} {Results} from a {Heterogeneous} {Four}-{Truck} {Platoon}},
	url = {https://www.sae.org/publications/technical-papers/content/2021-01-0071/},
	abstract = {Platooning has the potential to reduce greenhouse gas emissions of heavy-duty vehicles. Prior platooning studies have chiefly focused on the fuel economy characteristics of two- and three-truck platoons, and most have investigated aerodynamically homogeneous platoons with trucks of the same trim. Fo},
	language = {English},
	urldate = {2024-06-20},
	publisher = {SAE Technical Paper},
	author = {Stegner, Evan and Ward, Jacob and Siefert, Jan and Hoffman, Mark and Bevly, David M.},
	month = apr,
	year = {2021},
	doi = {10.4271/2021-01-0071},
}

Platooning has the potential to reduce greenhouse gas emissions of heavy-duty vehicles. Prior platooning studies have chiefly focused on the fuel economy characteristics of two- and three-truck platoons, and most have investigated aerodynamically homogeneous platoons with trucks of the same trim. Fo

@inproceedings{strong_utilizing_2021,
	series = {Modeling, {Estimation} and {Control} {Conference} {MECC} 2021},
	title = {Utilizing {Hidden} {Markov} {Models} to {Classify} {Maneuvers} and {Improve} {Estimates} of an {Unmanned} {Aerial} {Vehicle}},
	volume = {54},
	url = {https://www.sciencedirect.com/science/article/pii/S2405896321022588},
	doi = {10.1016/j.ifacol.2021.11.214},
	abstract = {Estimating the states of a Unmanned Aerial Vehicle (UAV) without the use of onboard sensors can be difficult, particularly if the UAV is performing high dynamic maneuvers. This paper examines if data driven modelling can assist in estimating UAV states, as well as classification of UAV maneuvers. A standard Extended Kalman Filter (EKF) that uses radar measurements and a constant acceleration dynamic model is used as the baseline estimation technique for dynamic UAV maneuvers. The UAV maneuvers are then modelled as Hidden Markov Models (HMM), which classify maneuvers and generate additional state information in the form of acceleration and jerk estimates. These HMM estimates are incorporated into an EKF to create a fusion EKF+HMM. This paper evaluates the robustness of the HMM classification accuracy and compares the EKF+HMM to a standard EKF using both simulated and experimental data.},
	urldate = {2024-06-20},
	booktitle = {{IFAC}-{PapersOnLine}},
	author = {Strong, Amy K. and Martin, Scott M. and Bevly, David M.},
	month = jan,
	year = {2021},
	keywords = {Aerospace Estimation, Estimation, Filtering, Gaussian Mixture Model, Hidden Markov Model, Mechanical, Time Series Modelling},
	pages = {449--454},
}

Estimating the states of a Unmanned Aerial Vehicle (UAV) without the use of onboard sensors can be difficult, particularly if the UAV is performing high dynamic maneuvers. This paper examines if data driven modelling can assist in estimating UAV states, as well as classification of UAV maneuvers. A standard Extended Kalman Filter (EKF) that uses radar measurements and a constant acceleration dynamic model is used as the baseline estimation technique for dynamic UAV maneuvers. The UAV maneuvers are then modelled as Hidden Markov Models (HMM), which classify maneuvers and generate additional state information in the form of acceleration and jerk estimates. These HMM estimates are incorporated into an EKF to create a fusion EKF+HMM. This paper evaluates the robustness of the HMM classification accuracy and compares the EKF+HMM to a standard EKF using both simulated and experimental data.

@inproceedings{adam_performance_2021,
	address = {Warrendale, PA},
	title = {Performance of {DSRC} {V2V} {Communication} {Networks} in an {Autonomous} {Semi}-{Truck} {Platoon} {Application}},
	url = {https://www.sae.org/publications/technical-papers/content/2021-01-0156/},
	abstract = {Autonomy for multiple trucks to drive in a fixed-headway platoon formation is achieved by adding precision GPS and V2V communications to a conventional adaptive cruise control (ACC) system. The performance of the Cooperative ACC (CACC) system depends heavily on the reliability of the underlying V2V},
	language = {English},
	urldate = {2024-06-20},
	publisher = {SAE Technical Paper},
	author = {Adam, Cristian and Andres, Russell and Smyth, Brandon and Kleinow, Timothy and Grenn, Katharina and Lakshmanan, Sridhar and Richardson, Paul},
	month = apr,
	year = {2021},
	doi = {10.4271/2021-01-0156},
}

Autonomy for multiple trucks to drive in a fixed-headway platoon formation is achieved by adding precision GPS and V2V communications to a conventional adaptive cruise control (ACC) system. The performance of the Cooperative ACC (CACC) system depends heavily on the reliability of the underlying V2V

@inproceedings{adam_correlation_2021,
	address = {Warrendale, PA},
	title = {Correlation between {Sensor} {Performance}, {Autonomy} {Performance} and {Fuel}-{Efficiency} in {Semi}-{Truck} {Platoons}},
	url = {https://www.sae.org/publications/technical-papers/content/2021-01-0064/},
	abstract = {Semi-trucks, specifically class-8 trucks, have recently become a platform of interest for autonomy systems. Platooning involves multiple trucks following each other in close proximity, with only the lead truck being manually driven and the rest being controlled autonomously. This approach to semi-tr},
	language = {English},
	urldate = {2024-06-20},
	publisher = {SAE Technical Paper},
	author = {Adam, Cristian and Lakshmanan, Sridhar and Richardson, Paul and Stegner, Evan and Ward, Jacob and Hoffman, Mark and Bevly, David M.},
	month = apr,
	year = {2021},
	doi = {10.4271/2021-01-0064},
}

Semi-trucks, specifically class-8 trucks, have recently become a platform of interest for autonomy systems. Platooning involves multiple trucks following each other in close proximity, with only the lead truck being manually driven and the rest being controlled autonomously. This approach to semi-tr

@inproceedings{watts_cooperative_2021,
	title = {Cooperative {Vector} {Tracking} for {Localization} of {Vehicles} in {Challenging} {GNSS} {Signal} {Environments}},
	url = {https://ieeexplore.ieee.org/abstract/document/9564468},
	doi = {10.1109/ITSC48978.2021.9564468},
	abstract = {This paper presents a robust method of processing GNSS data for vehicle localization in degraded signal environments where conventional receivers struggle to accurately position. The method relies on cooperation between receivers that use vector tracking, an advanced signal processing architecture for GNSS. Cooperation is performed through an EKF algorithm that can be employed for standalone or cooperative navigation by coupling stochastic receiver dynamics together. Simulation results are presented that demonstrate vehicle positioning is accurately achieved with cooperation under low C/N0 ratio conditions where standalone vector tracking is not stable and improved by including more collaborating receivers to the algorithm. The simulation claims are validated experimentally with GPS test data from a four-vehicle platoon traveling on an interstate exchange that incurs signal blockages from bridges.},
	urldate = {2024-06-20},
	booktitle = {2021 {IEEE} {International} {Intelligent} {Transportation} {Systems} {Conference} ({ITSC})},
	author = {Watts, Tanner and Martin, Scott and Bevly, David},
	month = sep,
	year = {2021},
	keywords = {GNSS, Global navigation satellite system, Heuristic algorithms, Location awareness, Navigation, Receivers, Signal processing algorithms, Simulation, cooperative navigation, vector tracking},
	pages = {135--142},
}

This paper presents a robust method of processing GNSS data for vehicle localization in degraded signal environments where conventional receivers struggle to accurately position. The method relies on cooperation between receivers that use vector tracking, an advanced signal processing architecture for GNSS. Cooperation is performed through an EKF algorithm that can be employed for standalone or cooperative navigation by coupling stochastic receiver dynamics together. Simulation results are presented that demonstrate vehicle positioning is accurately achieved with cooperation under low C/N0 ratio conditions where standalone vector tracking is not stable and improved by including more collaborating receivers to the algorithm. The simulation claims are validated experimentally with GPS test data from a four-vehicle platoon traveling on an interstate exchange that incurs signal blockages from bridges.

@inproceedings{mifflin_autonomous_2021,
	title = {Autonomous {Direct} {Calibration} of an {Inertial} {Measurement} {Unit}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=17909},
	doi = {10.33012/2021.17909},
	abstract = {Sensor calibration is an important step in obtaining useful measurements for an autonomous vehicle. Sensor fusion, in particular, relies on the proper calibration of sensors. Autonomous vehicles are generally designed with a fixed sensor suite. However, this limits the placement and usage of the sensors. Additionally, a manual calibration routine is required before the vehicle can be used. This calibration routine needs to be performed by a set of trained experts to a high degree of precision that requires time and specialized instruments. To enable dynamic reconfiguration of sensors, this work proposes a novel online method to autonomously calibrate an inertial measurement unit (IMU) directly to the vehicle frame. Once the self-calibration has been performed, the other sensors on the vehicle can be calibrated relative to the IMU. The self-calibration is conducted in a two-stage process. First, a Gaussian Radial Basis Function Neural Network is used to emulate an IMU for an arbitrary fixed control point on the vehicle. Then, a constrained maximum likelihood search method performs an IMU-to-IMU calibration between an IMU placed on the body of the vehicle, and the emulated IMU at the control point. The IMU emulation method obtains high-fidelity acceleration estimates on both simulated and experimental data sets. The maximum likelihood search method obtains sensor position estimates within 2 mm of the true sensor location in every direction and within 0.1 degrees of the true sensor orientation for a battery of tests in simulation.},
	language = {en},
	urldate = {2024-06-20},
	author = {Mifflin, Gregory and Bevly, David},
	month = sep,
	year = {2021},
	pages = {1606--1617},
}

Sensor calibration is an important step in obtaining useful measurements for an autonomous vehicle. Sensor fusion, in particular, relies on the proper calibration of sensors. Autonomous vehicles are generally designed with a fixed sensor suite. However, this limits the placement and usage of the sensors. Additionally, a manual calibration routine is required before the vehicle can be used. This calibration routine needs to be performed by a set of trained experts to a high degree of precision that requires time and specialized instruments. To enable dynamic reconfiguration of sensors, this work proposes a novel online method to autonomously calibrate an inertial measurement unit (IMU) directly to the vehicle frame. Once the self-calibration has been performed, the other sensors on the vehicle can be calibrated relative to the IMU. The self-calibration is conducted in a two-stage process. First, a Gaussian Radial Basis Function Neural Network is used to emulate an IMU for an arbitrary fixed control point on the vehicle. Then, a constrained maximum likelihood search method performs an IMU-to-IMU calibration between an IMU placed on the body of the vehicle, and the emulated IMU at the control point. The IMU emulation method obtains high-fidelity acceleration estimates on both simulated and experimental data sets. The maximum likelihood search method obtains sensor position estimates within 2 mm of the true sensor location in every direction and within 0.1 degrees of the true sensor orientation for a battery of tests in simulation.

@inproceedings{campos-vega_navigation_2021,
	title = {Navigation through the {Processing} of {Android} {Data} with a {High}-{Order} {Kalman} {Filter}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=18042},
	doi = {10.33012/2021.18042},
	abstract = {This paper presents a fourth order Extended Kalman Filter (EKF) that processes Android smartphone data for positioning and navigation. The EKF utilizes GNSS, IMU, and magnetometer sensor outputs for correction to its states. Unlike traditional GPS/INS error state recursions, the EKF processes the IMU outputs through the measurement observation matrix. The highorder EKF includes Fault Detection and Exclusion (FDE) to remove erroneous measurements. The navigation algorithm was evaluated with Pixel 4 and Pixel 4XL training data provided by the Google Smartphone Decimeter Challenge. The experimental results indicate the smartphones’ GNSS chip receivers provide positions with accuracies of roughly 1.5 meters at a rate of 1 Hz. The high-order EKF provides positions with accuracies of roughly 3 meters at a rate of 100 Hz. Furthermore, the highorder EKF can accurately navigate under motion with the IMU and magnetometer sensors for 5 to 10 seconds without GNSS. In cases when the GNSS has position faults, the EKF successfully rejects the outliers with FDE and continues to navigate. Future work includes augmenting the EKF with an adaptive process noise tuning algorithm, including sensor bias states for the IMU and magnetometer sensors, and comparing the high-order EKF to a traditional GPS/INS error state filter.},
	language = {en},
	urldate = {2024-06-20},
	author = {Campos-Vega, Christian J. and Watts, Tanner M. and Martin, Scott M. and Chen, Howard and Bevly, David M.},
	month = sep,
	year = {2021},
	pages = {2957--2973},
}

This paper presents a fourth order Extended Kalman Filter (EKF) that processes Android smartphone data for positioning and navigation. The EKF utilizes GNSS, IMU, and magnetometer sensor outputs for correction to its states. Unlike traditional GPS/INS error state recursions, the EKF processes the IMU outputs through the measurement observation matrix. The highorder EKF includes Fault Detection and Exclusion (FDE) to remove erroneous measurements. The navigation algorithm was evaluated with Pixel 4 and Pixel 4XL training data provided by the Google Smartphone Decimeter Challenge. The experimental results indicate the smartphones’ GNSS chip receivers provide positions with accuracies of roughly 1.5 meters at a rate of 1 Hz. The high-order EKF provides positions with accuracies of roughly 3 meters at a rate of 100 Hz. Furthermore, the highorder EKF can accurately navigate under motion with the IMU and magnetometer sensors for 5 to 10 seconds without GNSS. In cases when the GNSS has position faults, the EKF successfully rejects the outliers with FDE and continues to navigate. Future work includes augmenting the EKF with an adaptive process noise tuning algorithm, including sensor bias states for the IMU and magnetometer sensors, and comparing the high-order EKF to a traditional GPS/INS error state filter.

@inproceedings{boler_multispectral_2021,
	title = {Multispectral {Visual}-{Inertial} {Navigation} {Using} a {Dual}-{Layer} {Estimator} and {Targeted} {Histogram} {Equalization}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=18082},
	doi = {10.33012/2021.18082},
	abstract = {The fusion of a camera and an inertial measurement unit (IMU) is a rapidly-growing approach to GPS-denied navigation due to its minimal size, weight, and power requirements. In order to become a standard approach to for robust GPS-denied navigation, visual-inertial estimation must be able to perform in all situations, especially those present in challenging environments. Despite the popularity and wide-reaching applicability of the field, most visual-inertial research has focused on a standard platform and problem of a small aerial vehicle equipped with a machine-vision camera and inexpensive IMU operating in a well-lit indoor environment. As a result, the literature on extending visual-inertial estimation to illumination-challenged environments such as poorly-lit indoor scenarios and nighttime outdoor scenarios is shallow. These situations present significant challenges to visual navigation systems as their lack of contrast and illumination results in a reduced ability to extract and match features, therefore reducing the availability of valid visual measurements. To enable operation in such challenging situations, this paper presents a visual-inertial estimator which successfully operates with a visual-spectrum camera in poorly-lit environments and a thermal-infrared camera in illumination-denied environments. This success is achieved by a modification of the standard visual feature extraction and matching process which improves the robustness of features to contrast and illumination changes. After matching and processing such features, further robustness and accuracy improvements are achieved by the implementation of a dual-layer estimator which employs a robust and efficient EKF-based frontend to preprocess and validate incoming measurements before passing them into a batch least-squares optimizing backend. Solutions from the backend are periodically fed back into the frontend to correct accumulated error and maintain accurate real-time state estimates.},
	language = {en},
	urldate = {2024-06-20},
	author = {Boler, Matthew and Martin, Scott},
	month = sep,
	year = {2021},
	pages = {3149--3161},
}

The fusion of a camera and an inertial measurement unit (IMU) is a rapidly-growing approach to GPS-denied navigation due to its minimal size, weight, and power requirements. In order to become a standard approach to for robust GPS-denied navigation, visual-inertial estimation must be able to perform in all situations, especially those present in challenging environments. Despite the popularity and wide-reaching applicability of the field, most visual-inertial research has focused on a standard platform and problem of a small aerial vehicle equipped with a machine-vision camera and inexpensive IMU operating in a well-lit indoor environment. As a result, the literature on extending visual-inertial estimation to illumination-challenged environments such as poorly-lit indoor scenarios and nighttime outdoor scenarios is shallow. These situations present significant challenges to visual navigation systems as their lack of contrast and illumination results in a reduced ability to extract and match features, therefore reducing the availability of valid visual measurements. To enable operation in such challenging situations, this paper presents a visual-inertial estimator which successfully operates with a visual-spectrum camera in poorly-lit environments and a thermal-infrared camera in illumination-denied environments. This success is achieved by a modification of the standard visual feature extraction and matching process which improves the robustness of features to contrast and illumination changes. After matching and processing such features, further robustness and accuracy improvements are achieved by the implementation of a dual-layer estimator which employs a robust and efficient EKF-based frontend to preprocess and validate incoming measurements before passing them into a batch least-squares optimizing backend. Solutions from the backend are periodically fed back into the frontend to correct accumulated error and maintain accurate real-time state estimates.

@techreport{sarkar_final_2021,
	title = {Final {Technical} {Report} - {Fuel}-{Efficient} {Platooning} in {Mixed} {Traffic} {Highway} {Environments}},
	url = {https://www.osti.gov/biblio/1834543},
	abstract = {Platooning has become a focus area for heavy-duty vehicle fuel savings during highway driving. Often, the platoon formation is controlled by a system called Coordinated Adaptive Cruise Control (CACC). CACC platooning seeks aerodynamic fuel economy benefits while simultaneously decreasing driver strain by setting and maintaining a desired headway from preceding vehicles. Under close following conditions, the controller must exhibit robust characteristics during testing to be considered safe. Specific to this study, real-time vehicle to vehicle (V2V) communication shares vehicle state information among members of the same platoon, enhancing control response as the platoon members adjust to surrounding vehicles. Trucks not on the leading or trailing edge of the platoon exhibit benefits stemming from a push effect from the truck behind and a pull effect from the truck preceding it.},
	language = {English},
	number = {DOE-American Center for Mobility-0008470},
	urldate = {2024-06-20},
	institution = {American Center for Mobility, Ypsilanti, MI (United States)},
	author = {Sarkar, Reuben and Verma, Dhiren and Hoffman, Mark and Lakshmanan, Sridhar and Jakubowski, Beth},
	month = dec,
	year = {2021},
	doi = {10.2172/1834543},
}

Platooning has become a focus area for heavy-duty vehicle fuel savings during highway driving. Often, the platoon formation is controlled by a system called Coordinated Adaptive Cruise Control (CACC). CACC platooning seeks aerodynamic fuel economy benefits while simultaneously decreasing driver strain by setting and maintaining a desired headway from preceding vehicles. Under close following conditions, the controller must exhibit robust characteristics during testing to be considered safe. Specific to this study, real-time vehicle to vehicle (V2V) communication shares vehicle state information among members of the same platoon, enhancing control response as the platoon members adjust to surrounding vehicles. Trucks not on the leading or trailing edge of the platoon exhibit benefits stemming from a push effect from the truck behind and a pull effect from the truck preceding it.

@inproceedings{mcwilliams_magnetic_2021,
	title = {Magnetic {Localization} {Through} {INS} {Integration} and {Improvements} in {Map} {Matching}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=17906},
	doi = {10.33012/2021.17906},
	abstract = {Navigation by means of magnetic map-based particle filters has already been proven feasible in specific conditions and under strict adherance to mapped areas. Ambiguties inherent to the magnetic signal may be mitigated by fusing the filter with additional measurements, most accessibly from an accelerometer. Acceleration measurements can be used to improve the measurement update step by providing additional information for likelihood estimation. This approach was tested against a magnetometer-only filter and found improvements in the best-case and average performance, but greater variability in maximum error and decreased filter stability. Additionally, it was used to help gauge navigability and recoverability in instances of attempted localization not on the mapped route. Both approaches could recover from brief diversions from the map but could not overcome longer diversions that skipped segments of the map. Also introduced to help positioning estimation is spatial correlation analysis, a likelihood technique that takes into account multiple navigation samples and signal scaling. This technique is found to be competitive in accuracy but much more computationally demanding than the traditional aggregate bin likelihood technique.},
	language = {en},
	urldate = {2024-06-20},
	author = {McWilliams, Ryan and Chen, Howard and Kamrath, Luke and Bevly, David},
	month = sep,
	year = {2021},
	pages = {2272--2284},
}

Navigation by means of magnetic map-based particle filters has already been proven feasible in specific conditions and under strict adherance to mapped areas. Ambiguties inherent to the magnetic signal may be mitigated by fusing the filter with additional measurements, most accessibly from an accelerometer. Acceleration measurements can be used to improve the measurement update step by providing additional information for likelihood estimation. This approach was tested against a magnetometer-only filter and found improvements in the best-case and average performance, but greater variability in maximum error and decreased filter stability. Additionally, it was used to help gauge navigability and recoverability in instances of attempted localization not on the mapped route. Both approaches could recover from brief diversions from the map but could not overcome longer diversions that skipped segments of the map. Also introduced to help positioning estimation is spatial correlation analysis, a likelihood technique that takes into account multiple navigation samples and signal scaling. This technique is found to be competitive in accuracy but much more computationally demanding than the traditional aggregate bin likelihood technique.

@inproceedings{thompson_single_2021,
	title = {Single {Differenced} {Doppler} {Positioning} with {Low} {Earth} {Orbit} {Signals} of {Opportunity} and {Angle} of {Arrival} {Estimation}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=17845},
	doi = {10.33012/2021.17845},
	abstract = {This paper proposes a novel method for positioning using Low Earth Orbit (LEO) signals of opportunity. A stationary basestation and roving receiver framework is presented wherein the base-station performs Angle of Arrival (AOA) estimation of the LEO signals to obtain azimuth and elevation angles and shares them with a roving receiver. With the AOA estimates and differential Doppler positioning, there is no need for either the base station or roving receiver to have precise knowledge of the LEO satellite states. In this way, a constellation agnostic positioning approach that addresses one of the primary issues with navigation from signals of opportunity – the lack of knowledge of transmitter states – is developed. The accuracy requirements of the AOA estimates are investigated and the feasibility of this positioning method is discussed. The results of this analysis will show that with a single constellation, the range of noise on the AOA estimates that will produce acceptable position estimates is severely limited. As multiple constellations are used and the number of measurements increases, it becomes more resilient to distortion in the geometry matrix and noise on the Doppler measurements.},
	language = {en},
	urldate = {2024-06-20},
	author = {Thompson, Sterling and Martin, Scott and Bevly, David},
	month = jan,
	year = {2021},
	pages = {497--509},
}

This paper proposes a novel method for positioning using Low Earth Orbit (LEO) signals of opportunity. A stationary basestation and roving receiver framework is presented wherein the base-station performs Angle of Arrival (AOA) estimation of the LEO signals to obtain azimuth and elevation angles and shares them with a roving receiver. With the AOA estimates and differential Doppler positioning, there is no need for either the base station or roving receiver to have precise knowledge of the LEO satellite states. In this way, a constellation agnostic positioning approach that addresses one of the primary issues with navigation from signals of opportunity – the lack of knowledge of transmitter states – is developed. The accuracy requirements of the AOA estimates are investigated and the feasibility of this positioning method is discussed. The results of this analysis will show that with a single constellation, the range of noise on the AOA estimates that will produce acceptable position estimates is severely limited. As multiple constellations are used and the number of measurements increases, it becomes more resilient to distortion in the geometry matrix and noise on the Doppler measurements.

@unpublished{smith_evaluation_2020,
	title = {Evaluation of {Platooning} {Efficiency} for {Heavy} {Duty} {Trucks} using {Cooperative} {Adaptive} {Cruise} {Control}},
	copyright = {EMBARGO\_GLOBAL},
	url = {https://etd.auburn.edu//handle/10415/7241},
	abstract = {This thesis presents an evaluation of heavy duty truck platooning efficiency through fuel and coastdown testing. The trucking industry accounts for nearly 70\% of the freight shipped in the United States. These heavy duty vehicles travel on average 5x more miles than passenger vehicles and consume billions of gallons of fuel. The trucking industry has a large potential for vehicle automation to achieve benefits such as reduced traffic congestion, increased safety, and reduced fuel consumption and greenhouse gas emissions. Cooperative Adaptive Cruise Control (CACC) is a vehicle automation system that allows two or more vehicles to act cooperatively by using Vehicle 2 Vehicle communication. This thesis describes a CACC system implemented on two heavy duty trucks to travel in close proximity to each other, or platoon. The main benefit of CACC truck platooning is fuel savings from aerodynamic drag reduction.
The CACC system was evaluated through a series of test campaigns in order to study the benefits of truck platooning. An extensive fuel test was completed on a test track to study the fuel savings in a controlled environment. The nominal, aligned platoon was evaluated and the results were similar in magnitude and trends to prior work. Additionally, mixed traffic scenarios were tested with a forward pattern of passenger vehicles and a heavy duty truck to provide more realistic conditions like those experienced on-road. A novel aerodynamic evaluation, the controlled platoon coastdown, was then completed to quantify the drag area reduction of truck platooning. Previously, prior research described that coastdown testing could not be applied to platoons of vehicles because there is no method to maintain the gap distance between vehicles. In this thesis, the CACC system was modified to maintain the gap distance and complete a platoon coastdown in the lead and following vehicle positions. The drag area reductions for the following vehicle were distinct and significant in magnitude, 16.8 - 23.1\% for the gap distances tested. The calculated drag reductions were also converted to an estimated fuel savings for comparison to the fuel test, and the results were within 2.3\% of each other. In an effort to extend this work, a final test campaign was completed for on-road platooning. The highway fuel test is introduced, and the basic gravimetric results are presented. The fuel savings were lower than expected based on similar track-based tests, but the results are put into context with a study of the amount of traffic and platoon interactions. Future improvements to the CACC system and further evaluations of this truck platooning system are discussed.},
	language = {en},
	urldate = {2024-06-25},
	author = {Smith, Patrick},
	month = may,
	year = {2020},
	note = {Accepted: 2020-05-20T17:53:46Z},
}

This thesis presents an evaluation of heavy duty truck platooning efficiency through fuel and coastdown testing. The trucking industry accounts for nearly 70% of the freight shipped in the United States. These heavy duty vehicles travel on average 5x more miles than passenger vehicles and consume billions of gallons of fuel. The trucking industry has a large potential for vehicle automation to achieve benefits such as reduced traffic congestion, increased safety, and reduced fuel consumption and greenhouse gas emissions. Cooperative Adaptive Cruise Control (CACC) is a vehicle automation system that allows two or more vehicles to act cooperatively by using Vehicle 2 Vehicle communication. This thesis describes a CACC system implemented on two heavy duty trucks to travel in close proximity to each other, or platoon. The main benefit of CACC truck platooning is fuel savings from aerodynamic drag reduction. The CACC system was evaluated through a series of test campaigns in order to study the benefits of truck platooning. An extensive fuel test was completed on a test track to study the fuel savings in a controlled environment. The nominal, aligned platoon was evaluated and the results were similar in magnitude and trends to prior work. Additionally, mixed traffic scenarios were tested with a forward pattern of passenger vehicles and a heavy duty truck to provide more realistic conditions like those experienced on-road. A novel aerodynamic evaluation, the controlled platoon coastdown, was then completed to quantify the drag area reduction of truck platooning. Previously, prior research described that coastdown testing could not be applied to platoons of vehicles because there is no method to maintain the gap distance between vehicles. In this thesis, the CACC system was modified to maintain the gap distance and complete a platoon coastdown in the lead and following vehicle positions. The drag area reductions for the following vehicle were distinct and significant in magnitude, 16.8 - 23.1% for the gap distances tested. The calculated drag reductions were also converted to an estimated fuel savings for comparison to the fuel test, and the results were within 2.3% of each other. In an effort to extend this work, a final test campaign was completed for on-road platooning. The highway fuel test is introduced, and the basic gravimetric results are presented. The fuel savings were lower than expected based on similar track-based tests, but the results are put into context with a study of the amount of traffic and platoon interactions. Future improvements to the CACC system and further evaluations of this truck platooning system are discussed.

@unpublished{thopay_initialization_2020,
	title = {Initialization of a {Pedestrian} {Navigation} {System} {Using} a {Transfer} {Alignment} {Approach}},
	url = {https://etd.auburn.edu//handle/10415/7438},
	abstract = {Pedestrian navigation techniques are used to provide positioning information in lieu of or to supplement more traditional systems such as GNSS. A challenge facing users of pedestrian navigation algorithms is the acquisition of initialization data. Existing initialization methods for pedestrian navigation methods assume the availability of GNSS position and velocity and of standstill periods that can be used to provide attitude information. This thesis presents a method that performs the attitude initialization for a pedestrian navigation system (PNS) while the pedestrian is riding inside a vehicle. An algorithm is presented which uses data from a vehicle-mounted IMU and a pedestrian-mounted IMU to detect when the two sensors form a rigid body. Once rigidity has been established, a solution to Wahba’s Problem is used to solve for the misalignment between the two systems. The misalignment is used in conjunction with the vehicle’s attitude to initialize the PNS before the pedestrian leaves the vehicle. Performance analyses of the rigidity detector and misalignment estimation are shown using both simulated and real data, while a performance analysis for the PNS initialization procedure is shown using real data. The method is implemented using IMU data gathered using a Vectornav VN-300 GPS/INS and a Lincoln MKZ instrumented with a KVH 1750 IMU. Results show that the proposed method can initialize a PNS with a mean initial heading error of 7.3 degrees, with the error being attributable to violations of the rigidity condition.},
	language = {en},
	urldate = {2024-06-25},
	author = {Thopay, Archit},
	month = aug,
	year = {2020},
	note = {Accepted: 2020-08-11T18:03:13Z},
}

Pedestrian navigation techniques are used to provide positioning information in lieu of or to supplement more traditional systems such as GNSS. A challenge facing users of pedestrian navigation algorithms is the acquisition of initialization data. Existing initialization methods for pedestrian navigation methods assume the availability of GNSS position and velocity and of standstill periods that can be used to provide attitude information. This thesis presents a method that performs the attitude initialization for a pedestrian navigation system (PNS) while the pedestrian is riding inside a vehicle. An algorithm is presented which uses data from a vehicle-mounted IMU and a pedestrian-mounted IMU to detect when the two sensors form a rigid body. Once rigidity has been established, a solution to Wahba’s Problem is used to solve for the misalignment between the two systems. The misalignment is used in conjunction with the vehicle’s attitude to initialize the PNS before the pedestrian leaves the vehicle. Performance analyses of the rigidity detector and misalignment estimation are shown using both simulated and real data, while a performance analysis for the PNS initialization procedure is shown using real data. The method is implemented using IMU data gathered using a Vectornav VN-300 GPS/INS and a Lincoln MKZ instrumented with a KVH 1750 IMU. Results show that the proposed method can initialize a PNS with a mean initial heading error of 7.3 degrees, with the error being attributable to violations of the rigidity condition.

@unpublished{cofield_macn_2020,
	title = {{MACN}: {Map}-{Aided} {Cooperative} {Inertial} {Navigation}},
	shorttitle = {{MACN}},
	url = {https://etd.auburn.edu//handle/10415/7230},
	abstract = {This thesis presents an inertial navigation system (INS) that leverages the global positioning system (GPS) and a sparse road network database to cooperatively localize ground vehicles within close proximity to one another. The algorithm that constitutes the core contribution is named MACIN, an acronym for map aided cooperative inertial navigation.

Increasing demand for driver assistance features in consumer ground vehicles has spurred demand for ubiquitous high-accuracy absolute positioning. Accuracy at the lane level (under 1 meter) is required to execute complex operations such as maneuver planning. At the same time, standard automotive sensors such as cameras, inertial measurement units (IMUs), and GPS receivers do not provide this accuracy. Furthermore, common navigation techniques for fusing these sensor measurements, such as loose GPS/INS coupling in an extended Kalman filter (EKF), produce position performance that is consistently on the order of several meters in benign conditions.

MACIN comprises several improvements upon the loosely coupled GPS/INS EKF approach to acheive sub-meter accuracy and accurate lane determination. It uses sparse lane geometry information and lane sensing capability to apply position constraints along the earth tangent plane. The states of neighboring vehicles are estimated concurrently, and differential GPS is used to relate their states to one another. Lastly, Rao-Blackwellized particle filtering (RBPF) is used to estimate position with particles, while all other variables within the state are estimated with standard linearized filtering.

The success of these improvements is measured by reduction of positional error along the earth tangent plane. MACIN’s performance is compared to that of a loosely coupled GPS/INS EKF in both highway and suburban conditions. This thesis shows that the proposed novel filter consistently reduces error from 1-3 meters to the submeter level.},
	language = {en},
	urldate = {2024-06-25},
	author = {Cofield, Robert},
	month = may,
	year = {2020},
	note = {Accepted: 2020-05-18T11:37:59Z},
}

This thesis presents an inertial navigation system (INS) that leverages the global positioning system (GPS) and a sparse road network database to cooperatively localize ground vehicles within close proximity to one another. The algorithm that constitutes the core contribution is named MACIN, an acronym for map aided cooperative inertial navigation. Increasing demand for driver assistance features in consumer ground vehicles has spurred demand for ubiquitous high-accuracy absolute positioning. Accuracy at the lane level (under 1 meter) is required to execute complex operations such as maneuver planning. At the same time, standard automotive sensors such as cameras, inertial measurement units (IMUs), and GPS receivers do not provide this accuracy. Furthermore, common navigation techniques for fusing these sensor measurements, such as loose GPS/INS coupling in an extended Kalman filter (EKF), produce position performance that is consistently on the order of several meters in benign conditions. MACIN comprises several improvements upon the loosely coupled GPS/INS EKF approach to acheive sub-meter accuracy and accurate lane determination. It uses sparse lane geometry information and lane sensing capability to apply position constraints along the earth tangent plane. The states of neighboring vehicles are estimated concurrently, and differential GPS is used to relate their states to one another. Lastly, Rao-Blackwellized particle filtering (RBPF) is used to estimate position with particles, while all other variables within the state are estimated with standard linearized filtering. The success of these improvements is measured by reduction of positional error along the earth tangent plane. MACIN’s performance is compared to that of a loosely coupled GPS/INS EKF in both highway and suburban conditions. This thesis shows that the proposed novel filter consistently reduces error from 1-3 meters to the submeter level.

@unpublished{bryan_staying_2020,
	title = {Staying {Inside} the {Lines}: {Vehicle} {Agnostic} {Path} {Following} {Using} {Cascaded} {Adaptive} {Control}},
	shorttitle = {Staying {Inside} the {Lines}},
	url = {https://etd.auburn.edu//handle/10415/7527},
	abstract = {This thesis presents a vehicle agnostic steering controller for path following. Many active safety systems, such as collision avoidance and lane centering, as well as all SAE Level 2+ autonomous vehicles, rely on a lateral controller to follow a desired path. The vehicle agnostic path following controller presented in this thesis is comprised of two adaptive controllers in a cascaded architecture, with the outer loop controlling the path dynamics and the inner loop controlling the vehicle dynamics. First, some commonly used tire models and lateral vehicle models are introduced. Next, a sensitivity analysis is performed on a variety of lateral controllers under the influence of model uncertainties. This analysis is used to develop the vehicle agnostic path following controller, which is tested in simulation at multiple velocities on a sedan, an SUV, a pickup truck, and a minivan. In simulation, the controller is able to adapt to each platform and achieve good lane keeping performance around a curvy track at a wide range of speeds. The controller is then implemented and validated in real-time on a Lincoln MKZ, a Class-8 Peterbilt 579 cab, and a Peterbilt 579 with a loaded trailer. During a double lane change maneuver, the vehicle agnostic path following controller maintains maximum path tracking errors of approximately half a meter with all three of these setups. The controller is also implemented on a 1/10th scale RC car using a vision-based lane centering system to generate the reference path. Even on this scaled platform, the controller is able to follow the lane lines at multiple speeds, with maximum lookahead errors of 15 cm. Overall, the controller is shown to perform well on four simulated platforms and four experimental platforms at a range of longitudinal speeds, demonstrating the flexibility of the path following controller.},
	language = {en},
	urldate = {2024-06-25},
	author = {Bryan, William},
	month = nov,
	year = {2020},
	note = {Accepted: 2020-11-30T20:15:32Z},
}

This thesis presents a vehicle agnostic steering controller for path following. Many active safety systems, such as collision avoidance and lane centering, as well as all SAE Level 2+ autonomous vehicles, rely on a lateral controller to follow a desired path. The vehicle agnostic path following controller presented in this thesis is comprised of two adaptive controllers in a cascaded architecture, with the outer loop controlling the path dynamics and the inner loop controlling the vehicle dynamics. First, some commonly used tire models and lateral vehicle models are introduced. Next, a sensitivity analysis is performed on a variety of lateral controllers under the influence of model uncertainties. This analysis is used to develop the vehicle agnostic path following controller, which is tested in simulation at multiple velocities on a sedan, an SUV, a pickup truck, and a minivan. In simulation, the controller is able to adapt to each platform and achieve good lane keeping performance around a curvy track at a wide range of speeds. The controller is then implemented and validated in real-time on a Lincoln MKZ, a Class-8 Peterbilt 579 cab, and a Peterbilt 579 with a loaded trailer. During a double lane change maneuver, the vehicle agnostic path following controller maintains maximum path tracking errors of approximately half a meter with all three of these setups. The controller is also implemented on a 1/10th scale RC car using a vision-based lane centering system to generate the reference path. Even on this scaled platform, the controller is able to follow the lane lines at multiple speeds, with maximum lookahead errors of 15 cm. Overall, the controller is shown to perform well on four simulated platforms and four experimental platforms at a range of longitudinal speeds, demonstrating the flexibility of the path following controller.

@unpublished{brothers_path_2020,
	title = {Path {Following} and {Obstacle} {Avoidance} for {Autonomous} {Ground} {Vehicles} {Using} {Nonlinear} {Model} {Predictive} {Control}},
	url = {https://etd.auburn.edu//handle/10415/7236},
	abstract = {This thesis presents a nonlinear model predictive controller (NMPC) for path following and obstacle avoidance in automated driving systems. 
Automated safety control systems have been increasingly effective at reducing the number of traffic fatalities in the United States.
Many of the commercially available safety systems are still only classified as SAE level 1 and level 2 autonomy features.
To progress towards SAE level 3 and level 4 automated driving systems, obstacle avoidance control must be added to the vehicle's dynamic driving task, removing human drivers from the control loop.
Many current level 2 automated driving systems, such as Auburn University's heavy truck platooning system, could progress towards full autonomy by incorporating obstacle avoidance control into their existing control architectures.
The NMPC control module developed in this work is designed to take advantage of an automated vehicle's existing software stack to provide enhanced path tracking and obstacle avoidance maneuvering.

Two simple vehicle models, a kinematic model and a dynamic bicycle model, are developed identified and implemented in a flexible NMPC software library which is feasible for real-time control of an autonomous vehicle. 
In a series of simulation and real-time experiments, a detailed tuning procedure and performance evaluation for both NMPC implementations are given. 
The kinematic model implementation is also shown to work as a replacement controller in Auburn University's existing software architecture for long distance, non-line-of-sight following of a manually driven leader vehicle. Obstacle avoidance is added to each controller implementation through a set of hard constraints. 
The feasibility of this constraint method is demonstrated with two simulated obstacle avoidance scenarios.
Future improvements to both the obstacle avoidance method and path tracking accuracy are discussed.},
	language = {en},
	urldate = {2024-06-25},
	author = {Brothers, Robert},
	month = may,
	year = {2020},
	note = {Accepted: 2020-05-18T21:30:47Z},
}

This thesis presents a nonlinear model predictive controller (NMPC) for path following and obstacle avoidance in automated driving systems. Automated safety control systems have been increasingly effective at reducing the number of traffic fatalities in the United States. Many of the commercially available safety systems are still only classified as SAE level 1 and level 2 autonomy features. To progress towards SAE level 3 and level 4 automated driving systems, obstacle avoidance control must be added to the vehicle's dynamic driving task, removing human drivers from the control loop. Many current level 2 automated driving systems, such as Auburn University's heavy truck platooning system, could progress towards full autonomy by incorporating obstacle avoidance control into their existing control architectures. The NMPC control module developed in this work is designed to take advantage of an automated vehicle's existing software stack to provide enhanced path tracking and obstacle avoidance maneuvering. Two simple vehicle models, a kinematic model and a dynamic bicycle model, are developed identified and implemented in a flexible NMPC software library which is feasible for real-time control of an autonomous vehicle. In a series of simulation and real-time experiments, a detailed tuning procedure and performance evaluation for both NMPC implementations are given. The kinematic model implementation is also shown to work as a replacement controller in Auburn University's existing software architecture for long distance, non-line-of-sight following of a manually driven leader vehicle. Obstacle avoidance is added to each controller implementation through a set of hard constraints. The feasibility of this constraint method is demonstrated with two simulated obstacle avoidance scenarios. Future improvements to both the obstacle avoidance method and path tracking accuracy are discussed.

@inproceedings{smith_analysis_2020,
	address = {Warrendale, PA},
	title = {Analysis of {On}-{Road} {Highway} {Testing} for a {Two} {Truck} {Cooperative} {Adaptive} {Cruise} {Control} ({CACC}) {Platoon}},
	url = {https://www.sae.org/publications/technical-papers/content/2020-01-5009/},
	abstract = {A Cooperative Adaptive Cruise Control (CACC) platooning system was developed and implemented on Class 8 heavy duty trucks. The system allows for longitudinal, or gap spacing, control of the vehicle, while lateral control is maintained by the driver. Many previous aerodynamic studies have shown a red},
	language = {English},
	urldate = {2024-06-20},
	publisher = {SAE Technical Paper},
	author = {Smith, Patrick and Bevly, David},
	month = mar,
	year = {2020},
	doi = {10.4271/2020-01-5009},
}

A Cooperative Adaptive Cruise Control (CACC) platooning system was developed and implemented on Class 8 heavy duty trucks. The system allows for longitudinal, or gap spacing, control of the vehicle, while lateral control is maintained by the driver. Many previous aerodynamic studies have shown a red

@inproceedings{bunderson_automated_2020,
	title = {Automated {Tuning} and {Calibration} for {Unmanned} {Ground} {Vehicles}},
	abstract = {A critical and time-consuming part of commissioning an unmanned ground vehicle (UGV) is tuning and calibrating the navigation and control systems. This involves selecting and modifying parameters for these systems to obtain a desired response. Tuning these parameters often requires experience or technical expertise that may not be readily available in a time of need. Even the simple task of measuring the mounting location of the sensors introduce opportunities for user error. In addition, the tuning parameters for these systems may change significantly between UGVs. These challenges motivate the need for automated tuning and calibration algorithms to set parameters without the interaction from a user. This work presents automated tuning and calibration approaches for UGVs.},
	language = {en},
	author = {Bunderson, Nate and Bevly, David and Costley, Austin and Bryan, William and Mifflin, Gregory and Balas, Cristian},
	year = {2020},
}

A critical and time-consuming part of commissioning an unmanned ground vehicle (UGV) is tuning and calibrating the navigation and control systems. This involves selecting and modifying parameters for these systems to obtain a desired response. Tuning these parameters often requires experience or technical expertise that may not be readily available in a time of need. Even the simple task of measuring the mounting location of the sensors introduce opportunities for user error. In addition, the tuning parameters for these systems may change significantly between UGVs. These challenges motivate the need for automated tuning and calibration algorithms to set parameters without the interaction from a user. This work presents automated tuning and calibration approaches for UGVs.

@inproceedings{wood_gps_2020,
	title = {{GPS} {Positioning} in {Reduced} {Coverage} {Environments} {Using} {Batched} {Doppler} and {Pseudorange} {Measurements}},
	url = {https://ieeexplore.ieee.org/abstract/document/9110186},
	doi = {10.1109/PLANS46316.2020.9110186},
	abstract = {This paper summarizes Doppler positioning and clock modeling. A combined pseudorange and Doppler measurement model is discussed, as well as implications of using Doppler for positioning with the GPS constellation. The combined Doppler and pseudorange algorithm is compared to the standard GPS positioning method, and the constraints on the Doppler positioning will be analyzed. The accuracy of the batched results is compared to GPS positioning. Results for various scenarios with varying satellite visibility are shown. The results of the batched solutions are compared to the performance of standard GPS positioning in different environments.},
	urldate = {2024-06-20},
	booktitle = {2020 {IEEE}/{ION} {Position}, {Location} and {Navigation} {Symposium} ({PLANS})},
	author = {Wood, Joshua and Thompson, Sterling and Martin, Scott and Bevly, David},
	month = apr,
	year = {2020},
	note = {ISSN: 2153-3598},
	keywords = {CSAC, Clock Coasting, Doppler, Extended Kalman Filter, GPS, Positioning},
	pages = {915--924},
}

This paper summarizes Doppler positioning and clock modeling. A combined pseudorange and Doppler measurement model is discussed, as well as implications of using Doppler for positioning with the GPS constellation. The combined Doppler and pseudorange algorithm is compared to the standard GPS positioning method, and the constraints on the Doppler positioning will be analyzed. The accuracy of the batched results is compared to GPS positioning. Results for various scenarios with varying satellite visibility are shown. The results of the batched solutions are compared to the performance of standard GPS positioning in different environments.

@inproceedings{watts_implementation_2020,
	title = {Implementation and {Analysis} of a {GPS} {Differential} {Vector} {Delay}/{Frequency} {Lock} {Loop}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=17144},
	doi = {10.33012/2020.17144},
	abstract = {A Differential Vector Delay/Frequency Lock Loop (DVDFLL) is proposed to combine the benefits of DGPS position accuracy and vector tracking robustness. The DVDFLL tracks a rover’s received satellite signals by coupling the relative solution between the rover and a base station to the base receiver’s scalar tracking loops. The DVDFLL algorithm is compared to the VDFLL and a DGPS aided VDFLL (DPS-VDFLL). Simulation and experimental results with the GPS L1 C/A civilian signal show that the DVDFLL can outperform the VDFLL in code tracking and maintain the same robustness as the VDFLL in carrier tracking. The experimental results also show the DVDFLL can maintain DGPS positioning accuracy. When the baseline between the base and rover exceeds 10 km, the DVDFLL begins to have poor carrier tracking performance.},
	language = {en},
	urldate = {2024-06-20},
	author = {Watts, Tanner M. and Martin, Scott M. and Bevly, David M.},
	month = jan,
	year = {2020},
	pages = {300--314},
}

A Differential Vector Delay/Frequency Lock Loop (DVDFLL) is proposed to combine the benefits of DGPS position accuracy and vector tracking robustness. The DVDFLL tracks a rover’s received satellite signals by coupling the relative solution between the rover and a base station to the base receiver’s scalar tracking loops. The DVDFLL algorithm is compared to the VDFLL and a DGPS aided VDFLL (DPS-VDFLL). Simulation and experimental results with the GPS L1 C/A civilian signal show that the DVDFLL can outperform the VDFLL in code tracking and maintain the same robustness as the VDFLL in carrier tracking. The experimental results also show the DVDFLL can maintain DGPS positioning accuracy. When the baseline between the base and rover exceeds 10 km, the DVDFLL begins to have poor carrier tracking performance.

@inproceedings{douglass_deep_2020,
	title = {Deep {Learned} {Multi}-{Modal} {Traffic} {Agent} {Predictions} for {Truck} {Platooning} {Cut}-{Ins}},
	url = {https://ieeexplore.ieee.org/abstract/document/9109809},
	doi = {10.1109/PLANS46316.2020.9109809},
	abstract = {Recent advances in Driver-Assisted Truck Platooning (DATP) have shown success in linking multiple trucks in leader-follower platoons using Cooperative Adaptive Cruise Control (CACC). Such set ups allow for closer spacing between trucks which leads to fuel savings. Given that frontal collisions are the most common type of highway accident for heavy trucks, one key issue to truck platooning is handling situations in which vehicles cut-in between platooning trucks. Having more accurate and quicker predictions would improve the safety and efficiency of truck platooning by allowing the control system to react to the intruder sooner and allow for proper spacing before the cutin occurs. Moreover, reduction in false-positives could prevent the CACC from reacting to cut-in vehicles too early, leading to increased benefit from DATP. In this paper, we implement a deep neural network that generates multimodal predictions of traffic agents around a truck platoon. The method uses Long Short-Term Memory networks in an ensemble architecture to predict possible future positions with attached probabilities of vehicles passing by a truck platoon for 5 second horizons. The network performance is compared to a baseline of common state-based predictors including the Constant Velocity Predictor, the Constant Acceleration Predictor, and the Constant Steer Predictor.},
	urldate = {2024-06-20},
	booktitle = {2020 {IEEE}/{ION} {Position}, {Location} and {Navigation} {Symposium} ({PLANS})},
	author = {Douglass, Samuel Paul and Martin, Scott and Jennings, Andrew and Chen, Howard and Bevly, David M.},
	month = apr,
	year = {2020},
	note = {ISSN: 2153-3598},
	keywords = {Deep Learning, Time Series Forecasting, Truck Platoon},
	pages = {688--697},
}

Recent advances in Driver-Assisted Truck Platooning (DATP) have shown success in linking multiple trucks in leader-follower platoons using Cooperative Adaptive Cruise Control (CACC). Such set ups allow for closer spacing between trucks which leads to fuel savings. Given that frontal collisions are the most common type of highway accident for heavy trucks, one key issue to truck platooning is handling situations in which vehicles cut-in between platooning trucks. Having more accurate and quicker predictions would improve the safety and efficiency of truck platooning by allowing the control system to react to the intruder sooner and allow for proper spacing before the cutin occurs. Moreover, reduction in false-positives could prevent the CACC from reacting to cut-in vehicles too early, leading to increased benefit from DATP. In this paper, we implement a deep neural network that generates multimodal predictions of traffic agents around a truck platoon. The method uses Long Short-Term Memory networks in an ensemble architecture to predict possible future positions with attached probabilities of vehicles passing by a truck platoon for 5 second horizons. The network performance is compared to a baseline of common state-based predictors including the Constant Velocity Predictor, the Constant Acceleration Predictor, and the Constant Steer Predictor.

@inproceedings{burchfield_performance_2020,
	title = {Performance {Analysis} of {Low} {SWaP}-{C} {Jamming} {Mitigation} {Methods} for {Commercial} {Applications}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=17676},
	doi = {10.33012/2020.17676},
	abstract = {With the growing reliance upon GPS in the civilian sector, GPS need to be resilient to accidental and intentional interference threats. The Newark Airport incident, COTS PPDs, and other cases are prime examples of the need for resilient PNT in the civilian market. This paper implements four low SWaP-C (size, weight, power, and cost) mitigation methods and compares them in an attempt to determine the best algorithm for assured PNT. The algorithms analyzed are wavelet-implemented adaptive notch filter (WANF), SVD based FIR power minimization, space-time adaptive processing (STAP), and adaptive noise canceling. The first two algorithms use a signal antenna, and last two algorithms use two antennas. The algorithms are compared against an array of jamming scenarios, all of which originate from 3 main jamming types: continuous wave (CW) tone, narrowband noise, and chirp. The comparison between algorithms is quantified by analytical carrier to noise power density(CC/NN0) degradation at different jammer to signal (JJ/SS) power ratios and center frequency offsets, bandwidths, and sweep rates. The “mitigated” signal data is processed with a GPS L1 C/A receiver, and the receiver’s signal tracking CC/NN0 estimate is used to validate the analytical solutions. The analytical solution holds true for the wavelet implemented algorithm, the SVD based algorithm and the spacetime adaptive processing algorithm, but breaks down for the adaptive noise canceling algorithm. The results are analyzed and the conclusions are drawn based on the results.},
	language = {en},
	urldate = {2024-06-20},
	author = {Burchfield, Scott and Martin, Scott and Bevly, David and Starling, Joshua},
	month = sep,
	year = {2020},
	pages = {3592--3611},
}

With the growing reliance upon GPS in the civilian sector, GPS need to be resilient to accidental and intentional interference threats. The Newark Airport incident, COTS PPDs, and other cases are prime examples of the need for resilient PNT in the civilian market. This paper implements four low SWaP-C (size, weight, power, and cost) mitigation methods and compares them in an attempt to determine the best algorithm for assured PNT. The algorithms analyzed are wavelet-implemented adaptive notch filter (WANF), SVD based FIR power minimization, space-time adaptive processing (STAP), and adaptive noise canceling. The first two algorithms use a signal antenna, and last two algorithms use two antennas. The algorithms are compared against an array of jamming scenarios, all of which originate from 3 main jamming types: continuous wave (CW) tone, narrowband noise, and chirp. The comparison between algorithms is quantified by analytical carrier to noise power density(CC/NN0) degradation at different jammer to signal (JJ/SS) power ratios and center frequency offsets, bandwidths, and sweep rates. The “mitigated” signal data is processed with a GPS L1 C/A receiver, and the receiver’s signal tracking CC/NN0 estimate is used to validate the analytical solutions. The analytical solution holds true for the wavelet implemented algorithm, the SVD based algorithm and the spacetime adaptive processing algorithm, but breaks down for the adaptive noise canceling algorithm. The results are analyzed and the conclusions are drawn based on the results.

@inproceedings{lammert_impact_2020,
	title = {Impact of {Lateral} {Alignment} on the {Energy} {Savings} of a {Truck} {Platoon}},
	url = {https://www.sae.org/content/2020-01-0594/},
	doi = {10.4271/2020-01-0594},
	urldate = {2024-06-20},
	author = {Lammert, Michael P. and McAuliffe, Brian and Smith, Patrick and Raeesi, Arash and Hoffman, Mark and Bevly, David},
	month = apr,
	year = {2020},
	pages = {2020--01--0594},
}

@inproceedings{mcauliffe_impact_2020,
	title = {Impact of {Mixed} {Traffic} on the {Energy} {Savings} of a {Truck} {Platoon}},
	volume = {2},
	url = {https://www.sae.org/content/2020-01-0679},
	doi = {10.4271/2020-01-0679},
	abstract = {{\textless}div class="section abstract"{\textgreater}{\textless}div class="htmlview paragraph"{\textgreater}A two-truck platoon based on a prototype cooperative adaptive cruise control 
                    (CACC) system was tested on a closed test track in a variety of realistic 
                    traffic and transient operating scenarios - conditions that truck platoons are 
                    likely to face on real highways. The fuel consumption for both trucks in the 
                    platoon was measured using the SAE J1321 gravimetric procedure as well as 
                    calibrated J1939 instantaneous fuel rate, serving as proxies to evaluate the 
                    impact of aerodynamic drag reduction under constant-speed conditions. These 
                    measurements demonstrate the effects of: the presence of a 
                    multiple-passenger-vehicle pattern ahead of and adjacent to the platoon, cut-in 
                    and cut-out manoeuvres by other vehicles, transient traffic, the use of 
                    mismatched platooned vehicles (van trailer mixed with flatbed trailer), and the 
                    platoon following another truck with adaptive cruise control (ACC). These 
                    scenarios are intended to address the possibility of “background aerodynamic 
                    platooning” impacting realized savings on public roads. Using calibrated J1939 
                    fuel rate analysis, fuel savings for curved track sections versus straight track 
                    sections were also evaluated for these scenarios, highlighting differences in 
                    the implementation of the CACC control strategies compared to a stock ACC 
                    implementation. The use of different trailer types and the presence of 
                    passenger-vehicle traffic patterns showed a measurable impact on platoon 
                    performance in some conditions, but the basic fuel savings trends were 
                    retained.{\textless}/div{\textgreater}{\textless}/div{\textgreater}},
	language = {en},
	urldate = {2024-06-20},
	booktitle = {{SAE} {International} {Journal} of {Advances} and {Current} {Practices} in {Mobility}},
	author = {McAuliffe, Brian and Raeesi, Arash and Lammert, Michael and Smith, Patrick and Hoffman, Mark and Bevly, David},
	month = apr,
	year = {2020},
	pages = {1472--1496},
}

\textlessdiv class="section abstract"\textgreater\textlessdiv class="htmlview paragraph"\textgreaterA two-truck platoon based on a prototype cooperative adaptive cruise control (CACC) system was tested on a closed test track in a variety of realistic traffic and transient operating scenarios - conditions that truck platoons are likely to face on real highways. The fuel consumption for both trucks in the platoon was measured using the SAE J1321 gravimetric procedure as well as calibrated J1939 instantaneous fuel rate, serving as proxies to evaluate the impact of aerodynamic drag reduction under constant-speed conditions. These measurements demonstrate the effects of: the presence of a multiple-passenger-vehicle pattern ahead of and adjacent to the platoon, cut-in and cut-out manoeuvres by other vehicles, transient traffic, the use of mismatched platooned vehicles (van trailer mixed with flatbed trailer), and the platoon following another truck with adaptive cruise control (ACC). These scenarios are intended to address the possibility of “background aerodynamic platooning” impacting realized savings on public roads. Using calibrated J1939 fuel rate analysis, fuel savings for curved track sections versus straight track sections were also evaluated for these scenarios, highlighting differences in the implementation of the CACC control strategies compared to a stock ACC implementation. The use of different trailer types and the presence of passenger-vehicle traffic patterns showed a measurable impact on platoon performance in some conditions, but the basic fuel savings trends were retained.\textless/div\textgreater\textless/div\textgreater

@inproceedings{arizabaleta_receiver_2020,
	title = {Receiver {Protocol} and {Pitfalls} of {NMA} and {SCA} {Processing} {Under} {Spoofing} {Conditions} for {Future} {GNSS} {Signals} {Authentication}},
	url = {https://www.ion.org/publications/abstract.cfm?articleID=17716},
	doi = {10.33012/2020.17716},
	urldate = {2024-06-20},
	author = {Arizabaleta, Markel and Pany, Thomas and Scuccato, Tommaso and Chiara, Andrea Dalla and O’Driscoll, Cillian and Hanley, Neil},
	month = oct,
	year = {2020},
	pages = {3766--3780},
}

@inproceedings{givhan_performance_2020,
	title = {Performance {Analysis} of a {Vector} {Tracking} {Software} {Defined} {Receiver} for {GPS} {L5}},
	url = {https://www.ion.org/publications/abstract.cfm?articleID=17711},
	doi = {10.33012/2020.17711},
	urldate = {2024-06-20},
	author = {Givhan, Charles Anderson and Bevly, David M. and Martin, Scott M.},
	month = oct,
	year = {2020},
	pages = {3163--3179},
}

@unpublished{tabb_multi-antenna_2019,
	title = {Multi-{Antenna} {GPS} for {Improved} {Carrier} {Phase} {Positioning} in {Autonomous} {Convoys}},
	url = {https://etd.auburn.edu//handle/10415/6900},
	abstract = {In this thesis, low-cost differential Global Positioning System (DGPS) techniques are
developed for use in automated vehicle convoying.  Global Positioning System (GPS)
pseudorange and carrier-phase measurements are used to determine a relative position vector
(RPV) between vehicles and between two antennas rigidly  fixed to a vehicle in an attitude-baseline
con guration. The pseudorange measurements assist in the estimation of the integer
ambiguity inherent in the highly accurate, but ambiguous carrier-phase measurement
necessary to achieve centimeter-level relative positioning accuracy. A technique, referred
to as Dynamic Base Real Time Kinematic (DRTK) positioning, is described in detail to
estimate the carrier-phase ambiguity to ultimately provide a relative position vector estimate
between GPS antennas. DRTK is capable of providing relative positioning with L1, L2, and
L5 frequencies standalone or in combination with one another. Performance improves with
an increasing number of satellites in view and number of frequencies tracked per satellite.
In this thesis, DRTK is aided by including an a priori baseline magnitude between
antennas in a fixed attitude-baseline configuration on a single vehicle as a constraint with a
technique referred to as Fixed Attitude-baseline DRTK (FAD). The RPV and relative integer
ambiguities between these two  fixed antennas, referred to as the base and auxiliary antenna,
are computed and used to derive additional measurements between the base antenna and
a rover antenna on a separate vehicle via vector addition (FAD+DRTK). This approach
improves the availability of the solution by reducing the time-to-first-fix (TTFF) by one half
when compared against DRTK with two receivers. A comparative study of FAD+DRTK
and the conventional DRTK algorithm is presented when using low-cost single-frequency
receivers.},
	language = {en},
	urldate = {2024-06-25},
	author = {Tabb, Thomas Troupe},
	month = jul,
	year = {2019},
	note = {Accepted: 2019-07-29T19:34:28Z},
}

In this thesis, low-cost differential Global Positioning System (DGPS) techniques are developed for use in automated vehicle convoying. Global Positioning System (GPS) pseudorange and carrier-phase measurements are used to determine a relative position vector (RPV) between vehicles and between two antennas rigidly fixed to a vehicle in an attitude-baseline con guration. The pseudorange measurements assist in the estimation of the integer ambiguity inherent in the highly accurate, but ambiguous carrier-phase measurement necessary to achieve centimeter-level relative positioning accuracy. A technique, referred to as Dynamic Base Real Time Kinematic (DRTK) positioning, is described in detail to estimate the carrier-phase ambiguity to ultimately provide a relative position vector estimate between GPS antennas. DRTK is capable of providing relative positioning with L1, L2, and L5 frequencies standalone or in combination with one another. Performance improves with an increasing number of satellites in view and number of frequencies tracked per satellite. In this thesis, DRTK is aided by including an a priori baseline magnitude between antennas in a fixed attitude-baseline configuration on a single vehicle as a constraint with a technique referred to as Fixed Attitude-baseline DRTK (FAD). The RPV and relative integer ambiguities between these two fixed antennas, referred to as the base and auxiliary antenna, are computed and used to derive additional measurements between the base antenna and a rover antenna on a separate vehicle via vector addition (FAD+DRTK). This approach improves the availability of the solution by reducing the time-to-first-fix (TTFF) by one half when compared against DRTK with two receivers. A comparative study of FAD+DRTK and the conventional DRTK algorithm is presented when using low-cost single-frequency receivers.

@unpublished{ray_pedestrian_2019,
	title = {Pedestrian {Navigation} using {Particle} {Filtering} and a priori {Building} {Maps}},
	url = {https://etd.auburn.edu//handle/10415/6737},
	abstract = {This thesis presents a new particle filter (PF) weight update method that improves the performance of indoor positioning systems. In standalone inertial pedestrian-dead-reckoning (PDR) systems, the position error grows with time due to the inertial measurement unit's (IMU) sensor errors. Often external measurements from GPS or radio networks (e.g. wireless local area network (WLAN), ultra-wide-band (UWB), Bluetooth low energy (BLE) etc.) are used to restrict the error growth. External measurements from infrastructure-based systems have inherent high costs and deployment time, thus they are not easily implemented. The presented work focuses on the development of a standalone wearable navigation system that does not depend on physical infrastructure. In order to constrain error growth without external measurements, other techniques have been developed that utilize building map information as a measurement. One method uses the building to provide a heading measurement to reduce the drift in the heading solution. This is based upon the behavior that pedestrians typically walk straight when walking in building corridors. Another method constrains the error based upon the knowledge that pedestrian motion is limited by building floorplans, (e.g. walls, floors, and other features). This technique uses PF estimation to fuse standalone PDR with map measurements to perform accurate pedestrian localization. These techniques along with the current PDR techniques and underlying algorithms are discussed in detail. Lastly, this work presents a comparison of PFs that utilize different particle propagation and weight update methods for indoor positioning systems. A new type of weight update is also introduced that provides more accurate localization. The performance of the new weight update method is proven with a performance evaluation that includes both simulated and experimental data. The results of this and a summary are provided.},
	language = {en},
	urldate = {2024-06-25},
	author = {Ray, Tanner},
	month = may,
	year = {2019},
	note = {Accepted: 2019-05-16T15:17:35Z},
}

This thesis presents a new particle filter (PF) weight update method that improves the performance of indoor positioning systems. In standalone inertial pedestrian-dead-reckoning (PDR) systems, the position error grows with time due to the inertial measurement unit's (IMU) sensor errors. Often external measurements from GPS or radio networks (e.g. wireless local area network (WLAN), ultra-wide-band (UWB), Bluetooth low energy (BLE) etc.) are used to restrict the error growth. External measurements from infrastructure-based systems have inherent high costs and deployment time, thus they are not easily implemented. The presented work focuses on the development of a standalone wearable navigation system that does not depend on physical infrastructure. In order to constrain error growth without external measurements, other techniques have been developed that utilize building map information as a measurement. One method uses the building to provide a heading measurement to reduce the drift in the heading solution. This is based upon the behavior that pedestrians typically walk straight when walking in building corridors. Another method constrains the error based upon the knowledge that pedestrian motion is limited by building floorplans, (e.g. walls, floors, and other features). This technique uses PF estimation to fuse standalone PDR with map measurements to perform accurate pedestrian localization. These techniques along with the current PDR techniques and underlying algorithms are discussed in detail. Lastly, this work presents a comparison of PFs that utilize different particle propagation and weight update methods for indoor positioning systems. A new type of weight update is also introduced that provides more accurate localization. The performance of the new weight update method is proven with a performance evaluation that includes both simulated and experimental data. The results of this and a summary are provided.

@unpublished{apperson_design_2019,
	title = {Design and {Evaluation} of {Cooperative} {Adaptive} {Cruise} {Control} {System} for {Heavy} {Freight} {Vehicles}},
	url = {https://etd.auburn.edu//handle/10415/7069},
	abstract = {This thesis describes the design, implementation, and evaluation of a Cooperative Adaptive Cruise Control (CACC) system for heavy freight trucks that seeks to provide a platform for future cooperative control and estimation schemes. The freight trucking industry is the primary method of transporting goods in the United States. Approximately 70 percent of all transported goods travel by freight trucking. It is estimated that the freight trucking industry in the US spends close to 10 billion dollars on fuel each year. Most of the industrys time and fuel is consumed on long interstate corridors. Due to the high volume of these vehicles, there is huge potential benefit for a collaborative scheme of control. This control algorithm can help vehicles reduce fuel consumption, emissions, driver fatigue, and traffic congestion. By reducing the inter-vehicle spacing and automating throttle and brakes, all of these goals can be accomplished. This control system is known as CACC and is particularity valuable for freight vehicles as they can see significant value from reduced air drag by staying within the wake of a preceding truck.
CACC systems have been in development for many years now and are beginning to be tested on real-world convoys. There is still some potential savings to be gained through controller optimization. To validate new control and estimation techniques a vehicle testing platform is required. The primary contribution of this work is in the development of a platform for future research and validation as a proof of concept. The system is comprised of a communication network between vehicles, a low-level brake and throttle controller, a range estimation scheme and a cascaded gap controller. Testing results from this system both in simulation and on-highway driving are presented and show fuel savings of approximately 2-3 percent. While the fuel savings achieved under this work are not as high as predicted, it is expected that with further controller optimization will yield results in line with that of other researchers. The vehicle platform developed, however, was shown to be stable and will provide a good basis for future research.},
	language = {en},
	urldate = {2024-06-25},
	author = {Apperson, William Grant},
	month = dec,
	year = {2019},
	note = {Accepted: 2019-12-12T17:18:05Z},
}

This thesis describes the design, implementation, and evaluation of a Cooperative Adaptive Cruise Control (CACC) system for heavy freight trucks that seeks to provide a platform for future cooperative control and estimation schemes. The freight trucking industry is the primary method of transporting goods in the United States. Approximately 70 percent of all transported goods travel by freight trucking. It is estimated that the freight trucking industry in the US spends close to 10 billion dollars on fuel each year. Most of the industrys time and fuel is consumed on long interstate corridors. Due to the high volume of these vehicles, there is huge potential benefit for a collaborative scheme of control. This control algorithm can help vehicles reduce fuel consumption, emissions, driver fatigue, and traffic congestion. By reducing the inter-vehicle spacing and automating throttle and brakes, all of these goals can be accomplished. This control system is known as CACC and is particularity valuable for freight vehicles as they can see significant value from reduced air drag by staying within the wake of a preceding truck. CACC systems have been in development for many years now and are beginning to be tested on real-world convoys. There is still some potential savings to be gained through controller optimization. To validate new control and estimation techniques a vehicle testing platform is required. The primary contribution of this work is in the development of a platform for future research and validation as a proof of concept. The system is comprised of a communication network between vehicles, a low-level brake and throttle controller, a range estimation scheme and a cascaded gap controller. Testing results from this system both in simulation and on-highway driving are presented and show fuel savings of approximately 2-3 percent. While the fuel savings achieved under this work are not as high as predicted, it is expected that with further controller optimization will yield results in line with that of other researchers. The vehicle platform developed, however, was shown to be stable and will provide a good basis for future research.

@inproceedings{ward_cooperative_2019,
	title = {Cooperative {Adaptive} {Cruise} {Control} ({CACC}) in {Controlled} and {Real}-{World} {Environments}: {Testing} and {Results}},
	shorttitle = {Cooperative {Adaptive} {Cruise} {Control} ({CACC}) in {Controlled} and {Real}-{World} {Environments}},
	url = {https://www.osti.gov/biblio/1834377},
	abstract = {The transportation industry annually travels more than 6 times as many miles as passenger vehicles. The fuel cost associated with this represents 38\% of the total marginal operating cost for this industry. As a result, industry’s interest in applications of autonomy have grown. One application of this technology is Cooperative Adaptive Cruise Control (CACC) using Dedicated Short-Range Communications (DSRC). Auburn University outfitted four class 8 vehicles, two Peterbilt 579’s and two M915’s, with a basic hardware suite, and software library to enable level 1 autonomy. These algorithms were tested in controlled environments, such as the American Center for Mobility (ACM), and on public roads, such as highway 280 in Alabama, and Interstates 275/696 in Michigan. This paper reviews the results of these real-world tests and discusses the anomalies and failures that occurred during testing.},
	language = {English},
	urldate = {2024-06-20},
	publisher = {American Center for Mobility},
	author = {Ward, Jacob and Smith, Patrick and Pierce, Dan and Bevly, David and Richardson, Paul and Lakshmanan, Sridhar and Argyris, Athanasios and Smyth, Brandon and Adam, Cristian and Heim, Scott},
	month = aug,
	year = {2019},
}

The transportation industry annually travels more than 6 times as many miles as passenger vehicles. The fuel cost associated with this represents 38% of the total marginal operating cost for this industry. As a result, industry’s interest in applications of autonomy have grown. One application of this technology is Cooperative Adaptive Cruise Control (CACC) using Dedicated Short-Range Communications (DSRC). Auburn University outfitted four class 8 vehicles, two Peterbilt 579’s and two M915’s, with a basic hardware suite, and software library to enable level 1 autonomy. These algorithms were tested in controlled environments, such as the American Center for Mobility (ACM), and on public roads, such as highway 280 in Alabama, and Interstates 275/696 in Michigan. This paper reviews the results of these real-world tests and discusses the anomalies and failures that occurred during testing.

@inproceedings{thopay_initialization_2019,
	title = {Initialization of a {Pedestrian} {Navigation} {System}: {A} {Transfer} {Alignment} {Approach}},
	shorttitle = {Initialization of a {Pedestrian} {Navigation} {System}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=16795},
	doi = {10.33012/2019.16795},
	abstract = {Pedestrian navigation techniques are used to provide PNT information in lieu of or to supplement more traditional systems such as GNSS. A challenge that faces users of pedestrian navigation algorithms is the acquisition of initialization data. Existing pedestrian navigation methods assume the availability of GNSS position and velocity and of standstill periods that can be used to provide attitude information. This paper presents novel methods which uses inertial and position information from a vehicle to initialize and calibrate a pedestrian navigation system. The accuracy of the initialization is assessed by examining the different pedestrian trajectories computed by each algorithm as the pedestrian dismounts and walks away from the vehicle. Preliminary data runs show that the new algorithms initialize the pedestrian navigation system with approximately 18° of heading accuracy.},
	language = {en},
	urldate = {2024-06-20},
	author = {Thopay, Archit and Bevly, David and Martin, Scott},
	month = apr,
	year = {2019},
	pages = {84--97},
}

Pedestrian navigation techniques are used to provide PNT information in lieu of or to supplement more traditional systems such as GNSS. A challenge that faces users of pedestrian navigation algorithms is the acquisition of initialization data. Existing pedestrian navigation methods assume the availability of GNSS position and velocity and of standstill periods that can be used to provide attitude information. This paper presents novel methods which uses inertial and position information from a vehicle to initialize and calibrate a pedestrian navigation system. The accuracy of the initialization is assessed by examining the different pedestrian trajectories computed by each algorithm as the pedestrian dismounts and walks away from the vehicle. Preliminary data runs show that the new algorithms initialize the pedestrian navigation system with approximately 18° of heading accuracy.

@inproceedings{carter_baseline_2019,
	title = {Baseline {Impact} on {Geolocation}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=17059},
	doi = {10.33012/2019.17059},
	abstract = {GPS signals are weak in nature and are often a target of electronic attacks that aim to manipulate or disable navigation systems. As unmanned aerial vehicles (UAVs) become more ubiquitous, the manipulation of GPS capable UAVs is becoming a greater threat to their use. One method of mitigating these attacks employs the use of multiple antenna arrays. These arrays are utilized in many GPS dependent systems. These GPS capable UAVs using multiple antennas are restricted to a short baseline multi-antenna system similar to Controlled Reception Pattern Arrays (CRPA) sizes. Differential GPS measurements are used for Angle of Arrival (AOA) calculations which are used to locate the threat in question. The AOA estimations and attitude are a function of the baseline of the multi-antenna array in use. This paper explores the analysis of multiple antenna baselines and the impact the chosen baseline length has on the estimation of the electronic threat location. Previously, threat locations have been estimated as shown in work by Gray, Thompson, Mahmood and others. Numerous papers focusing on geolocation of threats show results of long (defined as greater than carrier phase wavelength) baseline geolocation. Gray’s work focuses on AOA techniques involving a larger baseline array, which is not feasible on a compact UAV. The work done by Gray also focuses on a 2-dimensional system and does not reference any elevation change between emitter and receiver. Work done by Costa focuses on an aerial platform but uses a large baseline. Costa’s AOA estimation methods are evaluated with a system with one wavelength spacing between antennas. Ina addition to publications on large baseline arrays, there have been several publications focusing on uniform linear arrays and geolocation accuracy, as from Zahemia and Huang, but these do not consider the three dimensional geolocation. Prior work by Corderio shows different forms of UAV attitude estimation on a short baseline array but also includes additional sensors in the solution for the system. While different baselines are considered in Corderio’s work, his solutions are focused on the fusion of multiple sensors and not the impact the baseline has. A primary motivator for this paper is the fact that UAVs typically have a very limited capacity for additional electronics. As weight is added, power consumption of the UAV increases as flight times and speeds decrease. Keeping these limitations in mind, a multi-antenna system can become constrained by size and weight limitations on the given platform. This motivates using as few antennas as possible to minimize weight and explore the impact of baseline on the geolocation of threats. In addition to the effects of the baseline, UAVs using pathfinding designed to avoid electronic threats can still fall victim to the attack if the uncertainty of the geolocation is not considered. In addition to commercial use, this geolocation system could be law enforcement searching for threats. The uncertainty of the location of the threat is vital for law enforcement’s ability to locate and disable the source of the interference. This paper explores the impact the array has on geolocation. An antenna array capable of GPS attitude solutions is the only form of navigation sensor used. For the purpose of the paper, the baseline from antenna to antenna is limited from ten percent of the GPS L1 wavelength to just under the GPS L1 wavelength. The carrier phase differences between antenna pairs are the measurements used for the attitude to keep the attitude solution dependent on the same measurements. The attitude solution is solved in a least squares estimation resulting in the relative rotation of Euler angles from the body frame to the East North Up frame (ENU). The attitude of the UAV is solved after each GPS update. After producing an attitude solution, AOA estimation methods are used on the antenna array signals to produce AOAs for the observed signals. An assumption made here is the detection of the invalid signal has been done successfully. The invalid signal is then assumed as being excluded from the position and attitude solutions returning the system to a similar state before the threat is introduced. The AOA estimation is produced in the body frame of the UAV. The attitude estimation previously solved is combined with the AOA estimation and transformed to the global frame to be used in a least squares estimation across multiple time steps. The position, attitude and AOA errors are combined to create a threat geolocation error as a function of antenna baseline. The results of the geolocation confidence should be quantified by the standard deviation of the combined results. This standard deviation should be shown as a function of the antenna baselines. This information can be used in system design for autonomous UAVs and threat location devices to find the capabilities and limitations of the systems being designed.},
	language = {en},
	urldate = {2024-06-20},
	author = {Carter, Patrick R. and Starling, Josh and Martin, Scott and Bevly, David},
	month = sep,
	year = {2019},
	pages = {2588--2597},
}

GPS signals are weak in nature and are often a target of electronic attacks that aim to manipulate or disable navigation systems. As unmanned aerial vehicles (UAVs) become more ubiquitous, the manipulation of GPS capable UAVs is becoming a greater threat to their use. One method of mitigating these attacks employs the use of multiple antenna arrays. These arrays are utilized in many GPS dependent systems. These GPS capable UAVs using multiple antennas are restricted to a short baseline multi-antenna system similar to Controlled Reception Pattern Arrays (CRPA) sizes. Differential GPS measurements are used for Angle of Arrival (AOA) calculations which are used to locate the threat in question. The AOA estimations and attitude are a function of the baseline of the multi-antenna array in use. This paper explores the analysis of multiple antenna baselines and the impact the chosen baseline length has on the estimation of the electronic threat location. Previously, threat locations have been estimated as shown in work by Gray, Thompson, Mahmood and others. Numerous papers focusing on geolocation of threats show results of long (defined as greater than carrier phase wavelength) baseline geolocation. Gray’s work focuses on AOA techniques involving a larger baseline array, which is not feasible on a compact UAV. The work done by Gray also focuses on a 2-dimensional system and does not reference any elevation change between emitter and receiver. Work done by Costa focuses on an aerial platform but uses a large baseline. Costa’s AOA estimation methods are evaluated with a system with one wavelength spacing between antennas. Ina addition to publications on large baseline arrays, there have been several publications focusing on uniform linear arrays and geolocation accuracy, as from Zahemia and Huang, but these do not consider the three dimensional geolocation. Prior work by Corderio shows different forms of UAV attitude estimation on a short baseline array but also includes additional sensors in the solution for the system. While different baselines are considered in Corderio’s work, his solutions are focused on the fusion of multiple sensors and not the impact the baseline has. A primary motivator for this paper is the fact that UAVs typically have a very limited capacity for additional electronics. As weight is added, power consumption of the UAV increases as flight times and speeds decrease. Keeping these limitations in mind, a multi-antenna system can become constrained by size and weight limitations on the given platform. This motivates using as few antennas as possible to minimize weight and explore the impact of baseline on the geolocation of threats. In addition to the effects of the baseline, UAVs using pathfinding designed to avoid electronic threats can still fall victim to the attack if the uncertainty of the geolocation is not considered. In addition to commercial use, this geolocation system could be law enforcement searching for threats. The uncertainty of the location of the threat is vital for law enforcement’s ability to locate and disable the source of the interference. This paper explores the impact the array has on geolocation. An antenna array capable of GPS attitude solutions is the only form of navigation sensor used. For the purpose of the paper, the baseline from antenna to antenna is limited from ten percent of the GPS L1 wavelength to just under the GPS L1 wavelength. The carrier phase differences between antenna pairs are the measurements used for the attitude to keep the attitude solution dependent on the same measurements. The attitude solution is solved in a least squares estimation resulting in the relative rotation of Euler angles from the body frame to the East North Up frame (ENU). The attitude of the UAV is solved after each GPS update. After producing an attitude solution, AOA estimation methods are used on the antenna array signals to produce AOAs for the observed signals. An assumption made here is the detection of the invalid signal has been done successfully. The invalid signal is then assumed as being excluded from the position and attitude solutions returning the system to a similar state before the threat is introduced. The AOA estimation is produced in the body frame of the UAV. The attitude estimation previously solved is combined with the AOA estimation and transformed to the global frame to be used in a least squares estimation across multiple time steps. The position, attitude and AOA errors are combined to create a threat geolocation error as a function of antenna baseline. The results of the geolocation confidence should be quantified by the standard deviation of the combined results. This standard deviation should be shown as a function of the antenna baselines. This information can be used in system design for autonomous UAVs and threat location devices to find the capabilities and limitations of the systems being designed.

@inproceedings{watts_gps_2019,
	title = {A {GPS} and {GLONASS} {L1} {Vector} {Tracking} {Software}-{Defined} {Receiver}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=16686},
	doi = {10.33012/2019.16686},
	abstract = {There has been significant work on vector tracking loops for the GPS L1 C/A signal. The GLONASS L1 signal is very similar in structure to GPS L1 C/A, and the same vector algorithms can be applied to this signal. The advantages of vector tracking over traditional scalar tracking are briefly introduced along with the advantages of combining GPS and GLONASS in the receiver’s navigation estimator. The implementation of a vector software receiver is discussed where the code is tracked by a Vector Delay Lock Loop (VDLL), and the carrier is tracked by a Vector Frequency Lock Loop (VFLL) with Phase Lock Loop (PLL) aiding for each satellite channel. The PLL aiding allows the channel replicas to stay carrier phase locked. An Extended Kalman Filter (EKF) is used to operate the vector tracking algorithm. A Common Transmission Time (CTT) navigation implementation of GPS and GLONASS in the vector algorithm is discussed. Fault Detection and Exclusion (FDE) is implemented into the EKF to mitigate vector tracking’s noise sharing issues. A constellation signal blockage experiment is described, and results are shown. From the results, the GLONASS constellation can keep lock on the GPS constellation during a GPS outage when the combined GPS \& GLONASS vector algorithm with FDE is applied. The same is true when there is a GLONASS constellation outage and GPS is available. Additional performance results are shown to compare GPS, GLONASS, and GPS \& GLONASS vector software receivers in the presence of multipath and signal attenuation. It is concluded that combining GPS and GLONASS can aid each other’s tracking in challenging signal conditions, but precision can be lost in the tracking and navigation estimations of both constellations.},
	language = {en},
	urldate = {2024-06-20},
	author = {Watts, Tanner and Martin, Scott and Bevly, David},
	month = jan,
	year = {2019},
	pages = {162--176},
}

There has been significant work on vector tracking loops for the GPS L1 C/A signal. The GLONASS L1 signal is very similar in structure to GPS L1 C/A, and the same vector algorithms can be applied to this signal. The advantages of vector tracking over traditional scalar tracking are briefly introduced along with the advantages of combining GPS and GLONASS in the receiver’s navigation estimator. The implementation of a vector software receiver is discussed where the code is tracked by a Vector Delay Lock Loop (VDLL), and the carrier is tracked by a Vector Frequency Lock Loop (VFLL) with Phase Lock Loop (PLL) aiding for each satellite channel. The PLL aiding allows the channel replicas to stay carrier phase locked. An Extended Kalman Filter (EKF) is used to operate the vector tracking algorithm. A Common Transmission Time (CTT) navigation implementation of GPS and GLONASS in the vector algorithm is discussed. Fault Detection and Exclusion (FDE) is implemented into the EKF to mitigate vector tracking’s noise sharing issues. A constellation signal blockage experiment is described, and results are shown. From the results, the GLONASS constellation can keep lock on the GPS constellation during a GPS outage when the combined GPS & GLONASS vector algorithm with FDE is applied. The same is true when there is a GLONASS constellation outage and GPS is available. Additional performance results are shown to compare GPS, GLONASS, and GPS & GLONASS vector software receivers in the presence of multipath and signal attenuation. It is concluded that combining GPS and GLONASS can aid each other’s tracking in challenging signal conditions, but precision can be lost in the tracking and navigation estimations of both constellations.

@inproceedings{kauten_perception_2018,
	title = {A {Perception} {Augmentation} {System} for {Autonomous} {Vehicles}},
	url = {https://aisel.aisnet.org/sigdsa2018/4/},
	abstract = {We describe a system prototype for perception augmentation in autonomous vehicles. The system is built using a fully convolutional deep encoder-decoder architecture to map pixels with depth measures to semantic class labels. Class labels recombine with depth measures to produce a 3-dimensional semantic map of the objects in front of the vehicle. The map, simplified to highlight areas of importance (e.g., other vehicles, pedestrians), is shown to the passenger using a novel user interface. The map is also analyzed for potential risks to queue alerts to the passenger. Alerts are both:
(1) shown to the passenger using an addressable LED strip around the windshield, and (2) delivered to the passenger through a speaker.},
	author = {Kauten, Christian and Gupta, Ashish and Bevly, David and Qin, Xiao and Li, Han and Jenkins, Alison},
	month = dec,
	year = {2018},
}

We describe a system prototype for perception augmentation in autonomous vehicles. The system is built using a fully convolutional deep encoder-decoder architecture to map pixels with depth measures to semantic class labels. Class labels recombine with depth measures to produce a 3-dimensional semantic map of the objects in front of the vehicle. The map, simplified to highlight areas of importance (e.g., other vehicles, pedestrians), is shown to the passenger using a novel user interface. The map is also analyzed for potential risks to queue alerts to the passenger. Alerts are both: (1) shown to the passenger using an addressable LED strip around the windshield, and (2) delivered to the passenger through a speaker.

@unpublished{sprunger_maintaining_2018,
	title = {Maintaining the {Security} and {Availability} of a {Stream} of {Time}-{Dependent} {Secret} {Information} in an {Ad}-{Hoc} {Network}.},
	url = {https://etd.auburn.edu//handle/10415/6465},
	abstract = {In this thesis we present a system called Ad Hoc Security for maintaining the security and availability of a stream of time-dependent secret data in an ad-hoc network. Time-dependence refers to how each piece of data is only useful during a unique time window. The goal is to determine the effectiveness of the Ad Hoc Security system for distributing and securing secret information in a mobile ad-hoc network under a variety of connectivity scenarios, with different sets of behavior parameters. Ad Hoc Security makes use of threshold cryptography for both decryption of the data as well as authentication of the participating devices. It is implemented and tested in the network simulator called ns3. The results of these tests are compared to show how different connectivity scenarios and behavior parameters affect the overall performance and security. The tests demonstrate its ability to adaptively shift between higher security and higher reliability based on its surroundings. Ad Hoc Security is compared to a similar, theoretical system that is tuned for perfect reliability at the cost of security. Compared to the perfectly reliable system, Ad Hoc Security consistently has half the vulnerable time and half as much decryption material saved with a minimum (and often avoidable) decrease in reliability. Most of the unreliability was from rapid, random group separation that the system could not predict or adapt to fast enough. At the end we also present three potential ways of improving reliability.},
	language = {en},
	urldate = {2024-06-25},
	author = {Sprunger, John David},
	month = nov,
	year = {2018},
	note = {Accepted: 2018-11-15T18:51:44Z},
}

In this thesis we present a system called Ad Hoc Security for maintaining the security and availability of a stream of time-dependent secret data in an ad-hoc network. Time-dependence refers to how each piece of data is only useful during a unique time window. The goal is to determine the effectiveness of the Ad Hoc Security system for distributing and securing secret information in a mobile ad-hoc network under a variety of connectivity scenarios, with different sets of behavior parameters. Ad Hoc Security makes use of threshold cryptography for both decryption of the data as well as authentication of the participating devices. It is implemented and tested in the network simulator called ns3. The results of these tests are compared to show how different connectivity scenarios and behavior parameters affect the overall performance and security. The tests demonstrate its ability to adaptively shift between higher security and higher reliability based on its surroundings. Ad Hoc Security is compared to a similar, theoretical system that is tuned for perfect reliability at the cost of security. Compared to the perfectly reliable system, Ad Hoc Security consistently has half the vulnerable time and half as much decryption material saved with a minimum (and often avoidable) decrease in reliability. Most of the unreliability was from rapid, random group separation that the system could not predict or adapt to fast enough. At the end we also present three potential ways of improving reliability.

@unpublished{shaw_obstacle_2018,
	title = {Obstacle {Avoidance} of an {Unmanned} {Ground} {Vehicle} using a {Combined} {Approach} of {Model} {Predictive} {Control} and {Proportional} {Navigation}},
	url = {https://etd.auburn.edu//handle/10415/6538},
	abstract = {This thesis presents a new approach for the guidance and control of a UGV (Unmanned
Ground Vehicle). A special focus was placed on moving obstacles that interfere with the
planned path of the vehicle, this is due to the fact that the majority of obstacle avoidance
research has been completed on stationary objects. An obstacle avoidance algorithm was
developed using an integrated system involving Proportional Navigation (Pro-Nav) and a
Nonlinear Model Predictive Controller (NMPC). An obstacle avoidance variant of the ideal
proportional navigation law generates command lateral accelerations to avoid obstacles, while
the NMPC is used to track the reference trajectory given by the Pro-Nav. The NMPC utilizes
a lateral vehicle dynamic model along with a nonlinear tire model in order to issue control
inputs. In this application an obstacle avoidance algorithm can take over the control of a
vehicle until the obstacle is no longer a threat. Another application of a Pro-Nav and NMPC
algorithm was tested for leader/follower situations. The performance of the leader/follower
and obstacle avoidance algorithm is evaluated through different simulations.

Simulation of the performance of the PNCAG and NMPC algorithm was conducted us
ing two different simulation environments; MATLAB and Simulink Vehicle Dynamics Block
set. The MATLAB simulation validated the algorithm showing that it could be used to
accomplish obstacle avoidance. With the algorithm shown to be effective, it was placed into
the Vehicle Dynamics Blockset. The Vehicle Dynamics Blockset provided a higher fidelity
vehicle model to provide a more realistic simulation environment. In addition to obstacle
avoidance, simulation results verified the performance of a modified version of the PNCAG
and NMPC algorithm in a leader/follower scenario. The results show, the algorithm handled
the leader/follower and collision avoidance with reasonable error. Overall the algorithm was
also able to follow a lead vehicle throughout a double lane change as well as avoid collision
with a moving obstacle in four different scenarios.},
	language = {en},
	urldate = {2024-06-25},
	author = {Shaw, Ryan},
	month = dec,
	year = {2018},
	note = {Accepted: 2018-12-06T20:02:39Z},
}

This thesis presents a new approach for the guidance and control of a UGV (Unmanned Ground Vehicle). A special focus was placed on moving obstacles that interfere with the planned path of the vehicle, this is due to the fact that the majority of obstacle avoidance research has been completed on stationary objects. An obstacle avoidance algorithm was developed using an integrated system involving Proportional Navigation (Pro-Nav) and a Nonlinear Model Predictive Controller (NMPC). An obstacle avoidance variant of the ideal proportional navigation law generates command lateral accelerations to avoid obstacles, while the NMPC is used to track the reference trajectory given by the Pro-Nav. The NMPC utilizes a lateral vehicle dynamic model along with a nonlinear tire model in order to issue control inputs. In this application an obstacle avoidance algorithm can take over the control of a vehicle until the obstacle is no longer a threat. Another application of a Pro-Nav and NMPC algorithm was tested for leader/follower situations. The performance of the leader/follower and obstacle avoidance algorithm is evaluated through different simulations. Simulation of the performance of the PNCAG and NMPC algorithm was conducted us ing two different simulation environments; MATLAB and Simulink Vehicle Dynamics Block set. The MATLAB simulation validated the algorithm showing that it could be used to accomplish obstacle avoidance. With the algorithm shown to be effective, it was placed into the Vehicle Dynamics Blockset. The Vehicle Dynamics Blockset provided a higher fidelity vehicle model to provide a more realistic simulation environment. In addition to obstacle avoidance, simulation results verified the performance of a modified version of the PNCAG and NMPC algorithm in a leader/follower scenario. The results show, the algorithm handled the leader/follower and collision avoidance with reasonable error. Overall the algorithm was also able to follow a lead vehicle throughout a double lane change as well as avoid collision with a moving obstacle in four different scenarios.

@unpublished{selikoff_coupling_2018,
	title = {Coupling {GPS}/{INS} and {IMM} {Radar} {Tracking} {Algorithms} for {Precise} {Collaborative} {Ground} {Vehicle} {Navigation}},
	url = {https://etd.auburn.edu//handle/10415/6541},
	abstract = {This thesis describes a method of collaborative ground vehicle navigation utilizing shared
radar data to provide observations during periods of GPS degradation. Navigational errors that
typically arise from degraded GPS signals can be reduced by providing relative observations
between vehicles from an Interacting Multiple Model (IMM) radar tracking filter. Loosely coupled
GPS/INS Extended Kalman Filters provide navigation solutions for each vehicle. When a
vehicle experiences GPS outages, other vehicles provide external observations from the IMM
tracking filter to correct the INS solution and bound error growth during the outage. The IMM
tracking filter uses constant velocity, constant acceleration, and constant turn models in combination
to generate a tracking solution. An evaluation of the performance of the proposed
method is presented using both simulated and experimental data. The IMM tracking algorithm
is implemented using range, range-rate, and azimuth data from a Delphi electronically scanning
radar. Results show improved navigation performance when utilizing the relative observations
during GPS outages. Specifically, the drift of the INS solution is bounded by the external
measurements provided by the IMM tracking filter when GPS is unavailable. Results from
both simulated and experimental data sets show that the system provides drastic improvements
over standalone INS navigation, with up to a 94\% decrease in error on position. These results
demonstrate that the proposed combination of GPS/INS and Radar IMM algorithms constitute
a feasible method of maintaing navigational accuracy during GPS outages.},
	language = {en},
	urldate = {2024-06-25},
	author = {Selikoff, Joseph},
	month = dec,
	year = {2018},
	note = {Accepted: 2018-12-07T16:10:21Z},
}

This thesis describes a method of collaborative ground vehicle navigation utilizing shared radar data to provide observations during periods of GPS degradation. Navigational errors that typically arise from degraded GPS signals can be reduced by providing relative observations between vehicles from an Interacting Multiple Model (IMM) radar tracking filter. Loosely coupled GPS/INS Extended Kalman Filters provide navigation solutions for each vehicle. When a vehicle experiences GPS outages, other vehicles provide external observations from the IMM tracking filter to correct the INS solution and bound error growth during the outage. The IMM tracking filter uses constant velocity, constant acceleration, and constant turn models in combination to generate a tracking solution. An evaluation of the performance of the proposed method is presented using both simulated and experimental data. The IMM tracking algorithm is implemented using range, range-rate, and azimuth data from a Delphi electronically scanning radar. Results show improved navigation performance when utilizing the relative observations during GPS outages. Specifically, the drift of the INS solution is bounded by the external measurements provided by the IMM tracking filter when GPS is unavailable. Results from both simulated and experimental data sets show that the system provides drastic improvements over standalone INS navigation, with up to a 94% decrease in error on position. These results demonstrate that the proposed combination of GPS/INS and Radar IMM algorithms constitute a feasible method of maintaing navigational accuracy during GPS outages.

@unpublished{nelson_development_2018,
	title = {Development of {ANVEL} {HIL}/{SIL} {Simulation} {Environment} for {Rapid} {Prototyping} of {Navigation} {Algorithms}},
	url = {https://etd.auburn.edu//handle/10415/6219},
	abstract = {This thesis presents the development of a Hardware In the Loop/Software In the Loop (HIL/SIL) simulation environment with the purpose of testing Global Positioning System/Inertial Navigation System (GPS/INS) navigation units in ANVEL.  HIL/SIL test beds are widely popular research tools that allow researchers to combine high fidelity vehicle simulations with errors inherent to hardware implementation, providing more realistic simulations.  Researchers may therefore use these test beds further along in the design process with confidence the simulation is behaving as in the real-world, removing operators from the test environment until final stages of development when the technology is more fully proven.  The work presented in this thesis focuses on the development of a modular HIL/SIL test bed using software and hardware add-ons to the Autonomous Navigation Virtual Environment Laboratory (ANVEL), a high fidelity vehicle simulation environment.  The test bed is designed with the goal of testing GPS/INS navigation units, specifically the unit developed by Auburn's GAVLab.

The capabilities of ANVEL are extended through the use of a plugin to relay vehicle state information out of the simulation environment.  A second plugin is developed for software GPS simulation in which satellites are simulated using broadcast ephemeris data.  Ray tracing is made possible through ANVEL's physics engine, allowing the simulation to detect satellite obstructions. Vehicle state information from ANVEL is used to generate Inertial Measurement Unit (IMU) and Wheel Speed Sensor (WSS) data in software modules which corrupt the information according to error models derived from real-world sensors.  Hardware implementations for the GPS, IMU, and WSS modules are then developed to add realism to the test environment.  A Spectracom GPS simulator is used to provide Radio Frequency (RF) signal in real-time to the navigation unit using position and satellite availability information from ANVEL.  A serial interface is then developed such that the IMU module outputs a serial signal to emulate the real sensor. Finally, quadrature signals are generated using Pulse Width Modulators (PWMs) to represent encoder pulses from wheel speed sensors.  Each of the developed software and hardware modules are then validated in both static and dynamic test scenarios using error characteristics from sensors in the GAVLab navigation unit as benchmarks for comparison.  Results from validation demonstrate the test bed is capable of outputting realistic sensor measurements which may be used interchangeably with sensors in a navigation unit for the purpose of algorithm development.},
	language = {en},
	urldate = {2024-06-25},
	author = {Nelson, Brently},
	month = may,
	year = {2018},
	note = {Accepted: 2018-05-04T14:14:28Z},
}

This thesis presents the development of a Hardware In the Loop/Software In the Loop (HIL/SIL) simulation environment with the purpose of testing Global Positioning System/Inertial Navigation System (GPS/INS) navigation units in ANVEL. HIL/SIL test beds are widely popular research tools that allow researchers to combine high fidelity vehicle simulations with errors inherent to hardware implementation, providing more realistic simulations. Researchers may therefore use these test beds further along in the design process with confidence the simulation is behaving as in the real-world, removing operators from the test environment until final stages of development when the technology is more fully proven. The work presented in this thesis focuses on the development of a modular HIL/SIL test bed using software and hardware add-ons to the Autonomous Navigation Virtual Environment Laboratory (ANVEL), a high fidelity vehicle simulation environment. The test bed is designed with the goal of testing GPS/INS navigation units, specifically the unit developed by Auburn's GAVLab. The capabilities of ANVEL are extended through the use of a plugin to relay vehicle state information out of the simulation environment. A second plugin is developed for software GPS simulation in which satellites are simulated using broadcast ephemeris data. Ray tracing is made possible through ANVEL's physics engine, allowing the simulation to detect satellite obstructions. Vehicle state information from ANVEL is used to generate Inertial Measurement Unit (IMU) and Wheel Speed Sensor (WSS) data in software modules which corrupt the information according to error models derived from real-world sensors. Hardware implementations for the GPS, IMU, and WSS modules are then developed to add realism to the test environment. A Spectracom GPS simulator is used to provide Radio Frequency (RF) signal in real-time to the navigation unit using position and satellite availability information from ANVEL. A serial interface is then developed such that the IMU module outputs a serial signal to emulate the real sensor. Finally, quadrature signals are generated using Pulse Width Modulators (PWMs) to represent encoder pulses from wheel speed sensors. Each of the developed software and hardware modules are then validated in both static and dynamic test scenarios using error characteristics from sensors in the GAVLab navigation unit as benchmarks for comparison. Results from validation demonstrate the test bed is capable of outputting realistic sensor measurements which may be used interchangeably with sensors in a navigation unit for the purpose of algorithm development.

@unpublished{geiger_laterally_2018,
	title = {Laterally {String} {Stable} {Control} at {Large} {Following} {Distances} {Using} {DRTK} and {TDCP}},
	url = {https://etd.auburn.edu//handle/10415/6415},
	abstract = {This thesis examines the lateral string stability of vehicle convoys. String stability is a type of stability that relates specifically to interconnected systems. In the case of vehicle convoys, string stability examines how the convoy, or "string", as a whole reacts to disturbances applied to the lead vehicle. When a convoy is considered string unstable, the disturbances at the lead vehicle are propagated down the stream. This occurs even if each vehicle is locally stable. When a convoy is considered string stable, those disturbances are dampened out along the string of vehicles. The idea of string stability may be formulated as both longitudinal control and lateral control problems. A longitudinally unstable string has the possibility of a vehicle wrecking into its preceding or following vehicle. A laterally unstable string has the possibility of a vehicle running off the road or wrecking into a vehicle next to it. This thesis addresses ways to prevent string instability in a lateral sense. 

A classical cascaded control strategy is presented which uses feedback of lateral position error and vehicle heading error. The measurements of lateral position error and heading error are acquired using dynamic base real-time kinematic positioning solution (DRTK) and time-differencing of the carrier phase measurement for odometry (TDCP). This methodology for generating measurements allows the vehicles in the convoy to follow at much greater distances than if a camera/radar was used for measurement generation. With this architecture, a baseline control strategy where each vehicle in the convoy follows the ultimate lead vehicle is employed. This control strategy is compared against another control strategy where each vehicle in the convoy follows the immediate lead vehicle. The control strategies are compared for multiple simulation scenarios using the industry standard vehicle simulation software, CarSim. These scenarios examine a manually driven or an autonomously driven ultimate lead and three driving scenarios: a single lane change, a double lane change, and driving on the NCAT test track. Evaluations are made based on the lateral error along the string. The results show that the immediate lead following strategy is able to achieve lateral offsets which are nearly equal to the ultimate lead following strategy; therefore, the requirements of the convoy itself should be the deciding factor for which following strategy is employed.},
	language = {en},
	urldate = {2024-06-25},
	author = {Geiger, Stephen},
	month = aug,
	year = {2018},
	note = {Accepted: 2018-08-03T21:39:51Z},
}

This thesis examines the lateral string stability of vehicle convoys. String stability is a type of stability that relates specifically to interconnected systems. In the case of vehicle convoys, string stability examines how the convoy, or "string", as a whole reacts to disturbances applied to the lead vehicle. When a convoy is considered string unstable, the disturbances at the lead vehicle are propagated down the stream. This occurs even if each vehicle is locally stable. When a convoy is considered string stable, those disturbances are dampened out along the string of vehicles. The idea of string stability may be formulated as both longitudinal control and lateral control problems. A longitudinally unstable string has the possibility of a vehicle wrecking into its preceding or following vehicle. A laterally unstable string has the possibility of a vehicle running off the road or wrecking into a vehicle next to it. This thesis addresses ways to prevent string instability in a lateral sense. A classical cascaded control strategy is presented which uses feedback of lateral position error and vehicle heading error. The measurements of lateral position error and heading error are acquired using dynamic base real-time kinematic positioning solution (DRTK) and time-differencing of the carrier phase measurement for odometry (TDCP). This methodology for generating measurements allows the vehicles in the convoy to follow at much greater distances than if a camera/radar was used for measurement generation. With this architecture, a baseline control strategy where each vehicle in the convoy follows the ultimate lead vehicle is employed. This control strategy is compared against another control strategy where each vehicle in the convoy follows the immediate lead vehicle. The control strategies are compared for multiple simulation scenarios using the industry standard vehicle simulation software, CarSim. These scenarios examine a manually driven or an autonomously driven ultimate lead and three driving scenarios: a single lane change, a double lane change, and driving on the NCAT test track. Evaluations are made based on the lateral error along the string. The results show that the immediate lead following strategy is able to achieve lateral offsets which are nearly equal to the ultimate lead following strategy; therefore, the requirements of the convoy itself should be the deciding factor for which following strategy is employed.

@unpublished{carson_enhancement_2018,
	title = {Enhancement and {Defense} of {GPS} {Navigation} {Using} {Signal} {Processing} {Techniques}},
	url = {https://etd.auburn.edu//handle/10415/6075},
	abstract = {In this thesis methods of spoo ng prevention are developed to detect, identify, and
mitigate an attack against both networked and standalone GPS receivers. A network based
detection algorithm is introduced which combines existing network data and GPS receiver
outputs to create a dynamic threshold used as an indication of a spoo ng attack. Attack
mitigation is accomplished in the development of an interference cancellation algorithm. In
the event of an attack, correlators are designated to track the attacking signal and extract
critical parameters describing its power, phase, and frequency. These parameters are used
to create a replica of the incoming signal which is then subtracted from the bu ered raw
data. This process removes the interfering signal allowing recovery of the authentic signal
and computation of true receiver position. The anti-spoo ng routines evaluated in this thesis
have an advantage over other methods due to their robustness in a wide variety of situations
and their ability to mitigate an attack without any prior knowledge of the spoofer or the
spoofed signal characteristics.
Testing of the algorithms developed in this thesis is accomplished using various types
of simulated GPS data since live-sky testing in the GPS frequency band is restricted by
the Federal Communications Commission. Actual GPS measurements are collected and
modi ed to simulate spoo ng in tests of the detection algorithms. Sets of simulated GPS
data  les are combined in software to simulate spoo ng at the signal level. These data sets
are used to test the interference cancellation algorithm's e ectiveness at removing a spoofed
signal in the intermediate frequency (IF) stage. The detection and suppression algorithms
are demonstrated to e ectively alert the user to an attack and mitigate its e ect in IF stage
generating a cleaned data set for acquisition and tracking of the authentic GPS signal.},
	language = {en},
	urldate = {2024-06-25},
	author = {Carson, Nathaniel},
	month = feb,
	year = {2018},
	note = {Accepted: 2018-02-14T15:11:42Z},
}

In this thesis methods of spoo ng prevention are developed to detect, identify, and mitigate an attack against both networked and standalone GPS receivers. A network based detection algorithm is introduced which combines existing network data and GPS receiver outputs to create a dynamic threshold used as an indication of a spoo ng attack. Attack mitigation is accomplished in the development of an interference cancellation algorithm. In the event of an attack, correlators are designated to track the attacking signal and extract critical parameters describing its power, phase, and frequency. These parameters are used to create a replica of the incoming signal which is then subtracted from the bu ered raw data. This process removes the interfering signal allowing recovery of the authentic signal and computation of true receiver position. The anti-spoo ng routines evaluated in this thesis have an advantage over other methods due to their robustness in a wide variety of situations and their ability to mitigate an attack without any prior knowledge of the spoofer or the spoofed signal characteristics. Testing of the algorithms developed in this thesis is accomplished using various types of simulated GPS data since live-sky testing in the GPS frequency band is restricted by the Federal Communications Commission. Actual GPS measurements are collected and modi ed to simulate spoo ng in tests of the detection algorithms. Sets of simulated GPS data les are combined in software to simulate spoo ng at the signal level. These data sets are used to test the interference cancellation algorithm's e ectiveness at removing a spoofed signal in the intermediate frequency (IF) stage. The detection and suppression algorithms are demonstrated to e ectively alert the user to an attack and mitigate its e ect in IF stage generating a cleaned data set for acquisition and tracking of the authentic GPS signal.

@unpublished{williams_radar_2018,
	title = {Radar {Aided} {INS} {Navigation} {Filter} with {Magnetometer} {Based} {Attitude} {Measurements}},
	copyright = {EMBARGO\_GLOBAL},
	url = {https://etd.auburn.edu//handle/10415/6548},
	abstract = {This thesis presents a method for GPS-free navigation using a radar-aided inertial navigation
 filter with a magnetometer based attitude measurement. GPS has become the popular
tool of choice when considering navigation solutions today, however, GPS is a low-power signal
that can be easily blocked by large structures or jamming. Previous work has been done
on attitude and heading reference systems which use magnetometers and accelerometers to
determine the attitude of a vehicle. The magnetometer and accelerometer attitude measurement
can be incorporated into the measurement update of an Extended Kalman Filter
(EKF). The EKF presented in this thesis propagates the inertial navigation solution in the
time update, while the measurement update uses the radar and attitude measurements to
correct the inertial navigation system propagation errors.
In this thesis, magnetometer calibration will fi rst be discussed. A magnetometer calibration
routine will be selected then verified though simulated and experimental tests. Then,
an attitude determination algorithm that uses magnetometer and accelerometer measurements
will be reviewed and tested in simulation and with experimental data. Next, inertial
navigation system propagation errors will be discussed and how radar-aiding in an Extended
Kalman Filter can reduce propagation errors. Radar target determination is overviewed
next, and  finally, a new fi lter called the Radar-Aided INS (RAINS)  filter is proposed and
tested in simulation. The results of RAINS fi lter analysis show the possibility of navigation
completely independent of GPS. The radar used in this thesis is a Delphi Electronically
Scanning Radar which provides measurements of range, range rate, and azimuth.},
	language = {en},
	urldate = {2024-06-25},
	author = {Williams, John},
	month = dec,
	year = {2018},
	note = {Accepted: 2018-12-11T20:26:03Z},
}

This thesis presents a method for GPS-free navigation using a radar-aided inertial navigation filter with a magnetometer based attitude measurement. GPS has become the popular tool of choice when considering navigation solutions today, however, GPS is a low-power signal that can be easily blocked by large structures or jamming. Previous work has been done on attitude and heading reference systems which use magnetometers and accelerometers to determine the attitude of a vehicle. The magnetometer and accelerometer attitude measurement can be incorporated into the measurement update of an Extended Kalman Filter (EKF). The EKF presented in this thesis propagates the inertial navigation solution in the time update, while the measurement update uses the radar and attitude measurements to correct the inertial navigation system propagation errors. In this thesis, magnetometer calibration will fi rst be discussed. A magnetometer calibration routine will be selected then verified though simulated and experimental tests. Then, an attitude determination algorithm that uses magnetometer and accelerometer measurements will be reviewed and tested in simulation and with experimental data. Next, inertial navigation system propagation errors will be discussed and how radar-aiding in an Extended Kalman Filter can reduce propagation errors. Radar target determination is overviewed next, and finally, a new fi lter called the Radar-Aided INS (RAINS) filter is proposed and tested in simulation. The results of RAINS fi lter analysis show the possibility of navigation completely independent of GPS. The radar used in this thesis is a Delphi Electronically Scanning Radar which provides measurements of range, range rate, and azimuth.

@inproceedings{tabb_improved_2018,
	title = {{IMPROVED} {RELATIVE} {POSITIONING} {FOR} {PATH} {FOLLOWING} {IN} {AUTONOMOUS} {CONVOYS}},
	abstract = {This work presents the development of an algorithm to incorporate measurements from multiple antennas to improve the relative position solution between convoying vehicles provided by Global Positioning System (GPS) measurements. The technique presented, incorporates measurements from multiple antennas with a known fixed-baseline between a base antenna and auxiliary antenna on a base vehicle, and a rover antenna on a rover vehicle. The additional information provided by the fixed-baseline distance is used to provide an additional measurement with low uncertainty for improved integer ambiguity resolution between the base and auxiliary receiver, which in turn, provides additional measurements for determining the integer ambiguity difference between the base and rover receivers for the computation of a high-precision relative position vector (HPRPV).},
	language = {en},
	author = {Tabb, Thomas T and Martin, Scott and Bevly, David and Ratowski, Jeff},
	year = {2018},
}

This work presents the development of an algorithm to incorporate measurements from multiple antennas to improve the relative position solution between convoying vehicles provided by Global Positioning System (GPS) measurements. The technique presented, incorporates measurements from multiple antennas with a known fixed-baseline between a base antenna and auxiliary antenna on a base vehicle, and a rover antenna on a rover vehicle. The additional information provided by the fixed-baseline distance is used to provide an additional measurement with low uncertainty for improved integer ambiguity resolution between the base and auxiliary receiver, which in turn, provides additional measurements for determining the integer ambiguity difference between the base and rover receivers for the computation of a high-precision relative position vector (HPRPV).

@inproceedings{brothers_comparison_2018,
	title = {A {COMPARISON} {OF} {VEHICLE} {HANDLING} {FIDELITY} {BETWEEN} {THE} {GAZEBO} {AND} {ANVEL} {SIMULATORS}},
	abstract = {This paper provides a comparison of the Gazebo and ANVEL simulators and analyzes the aspects of vehicle modeling fidelity that are critical to the design of unmanned ground vehicle (UGV) control and estimation algorithms. The robotic simulators Gazebo [1], from the Open Source Robotics Foundation (OSRF), and Autonomous Navigation Virtual Environment Laboratory (ANVEL) [2], from Quantum Signal, are two popular new tools that are being used extensively in academic, commercial, and military development of perception, navigation, and control algorithms for UGVs. Despite the similarities between Gazebo and ANVEL there has been no direct comparison between the two simulators with respect to their validity as vehicle dynamics simulators.},
	language = {en},
	author = {Brothers, Robert},
	year = {2018},
}

This paper provides a comparison of the Gazebo and ANVEL simulators and analyzes the aspects of vehicle modeling fidelity that are critical to the design of unmanned ground vehicle (UGV) control and estimation algorithms. The robotic simulators Gazebo [1], from the Open Source Robotics Foundation (OSRF), and Autonomous Navigation Virtual Environment Laboratory (ANVEL) [2], from Quantum Signal, are two popular new tools that are being used extensively in academic, commercial, and military development of perception, navigation, and control algorithms for UGVs. Despite the similarities between Gazebo and ANVEL there has been no direct comparison between the two simulators with respect to their validity as vehicle dynamics simulators.

@inproceedings{ray_comparison_2018,
	title = {A {Comparison} of {Particle} {Propagation} and {Weight} {Update} {Methods} for {Indoor} {Positioning} {Systems}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=16075},
	doi = {10.33012/2018.16075},
	abstract = {This work is a comparison of Particle Filters (PFs) in the field of indoor positioning, that use different types of particle propagation and weight update methods. The PFs fuse standalone pedestrian dead-reckoning (PDR) and building maps to perform accurate pedestrian localization. This work proposes a new weight update method based upon the weaknesses of the current PF methods in certain situations. The situations of interest are when map only constrains the single side of the particle cloud. This occurs when a pedestrian moves along a wall in a wide corridor, or in a room where the outer wall is the only feature constraining the pedestrian’s motion. Current PF weight update methods shift the mean of the particle distribution away from the wall towards open space. This produces an undesired estimate that introduces drift into the position solution. The proposed method seeks to reduce this error to improve the navigation solution. A detailed performance evaluation of existing and new methods is presented using experimental data.},
	language = {en},
	urldate = {2024-06-20},
	author = {Ray, Tanner N. and Pierce, J. Dan and Bevly, David M.},
	month = sep,
	year = {2018},
	pages = {3398--3408},
}

This work is a comparison of Particle Filters (PFs) in the field of indoor positioning, that use different types of particle propagation and weight update methods. The PFs fuse standalone pedestrian dead-reckoning (PDR) and building maps to perform accurate pedestrian localization. This work proposes a new weight update method based upon the weaknesses of the current PF methods in certain situations. The situations of interest are when map only constrains the single side of the particle cloud. This occurs when a pedestrian moves along a wall in a wide corridor, or in a room where the outer wall is the only feature constraining the pedestrian’s motion. Current PF weight update methods shift the mean of the particle distribution away from the wall towards open space. This produces an undesired estimate that introduces drift into the position solution. The proposed method seeks to reduce this error to improve the navigation solution. A detailed performance evaluation of existing and new methods is presented using experimental data.

@inproceedings{williams_radar-aided_2018,
	title = {Radar-{Aided} {INS} with {Magnetometer} {Attitude} {Determination}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=16015},
	doi = {10.33012/2018.16015},
	abstract = {GPS has become a popular measurement choice for navigation solutions today because of it long term stability and worldwide availability. However, GPS is a low-power signal that can be easily blocked by large structures or jamming. Without GPS, many consumer-grade sensors are unable to provide accurate navigation solutions because of noise and bias errors. This paper presents a method for a GPS-free navigation solution by using a magnetometer-aided, radar/INS coupled filter for vehicle navigation. Previous work has been done on attitude-heading reference systems which use magnetometers and accelerometers to determine the attitude of a vehicle. This attitude measurement can be incorporated in to the measurement update of an EKF. The main contribution of this paper is a radar aided INS EKF that will propagate the INS solutions in the time update, while the measurement update will use the radar measurement Jacobian and the attitude measurement to correct the INS propagations errors. Results in simulation and with real-world data show that this filter is capable of estimating the position, velocity, and attitude of a vehicle by constraining the error associated with pure INS propagation. The radar used in this paper is a Delphi Electronically Scanning Radar, and provides measurements for range, range rate, and azimuth.},
	language = {en},
	urldate = {2024-06-20},
	author = {Williams, John and Martin, Scott M. and Bevly, David},
	month = sep,
	year = {2018},
	pages = {1985--1998},
}

GPS has become a popular measurement choice for navigation solutions today because of it long term stability and worldwide availability. However, GPS is a low-power signal that can be easily blocked by large structures or jamming. Without GPS, many consumer-grade sensors are unable to provide accurate navigation solutions because of noise and bias errors. This paper presents a method for a GPS-free navigation solution by using a magnetometer-aided, radar/INS coupled filter for vehicle navigation. Previous work has been done on attitude-heading reference systems which use magnetometers and accelerometers to determine the attitude of a vehicle. This attitude measurement can be incorporated in to the measurement update of an EKF. The main contribution of this paper is a radar aided INS EKF that will propagate the INS solutions in the time update, while the measurement update will use the radar measurement Jacobian and the attitude measurement to correct the INS propagations errors. Results in simulation and with real-world data show that this filter is capable of estimating the position, velocity, and attitude of a vehicle by constraining the error associated with pure INS propagation. The radar used in this paper is a Delphi Electronically Scanning Radar, and provides measurements for range, range rate, and azimuth.

@inproceedings{selikoff_collaborative_2018,
	title = {Collaborative {Ground} {Vehicle} {Navigation} {Utilizing} an {IMM} {Radar} {Tracking} {Algorithm}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=15844},
	doi = {10.33012/2018.15844},
	abstract = {This work proposes a method of collaborative ground vehicle navigation utilizing shared radar data to provide observations during periods of GPS degradation. Navigational errors that typically arise from degraded GPS signals are reduced by providing relative observations between vehicles from an Interacting Multiple Model (IMM) radar tracking filter. Loosely coupled GPS/INS Extended Kalman Filters provide navigation solutions for each vehicle. When a vehicle experiences GPS outages, other vehicles provide external observations from the IMM tracking filter to correct the INS solution and bound error growth during the outage. The IMM tracking filter uses constant velocity, constant acceleration, and constant turn models in combination to generate a tracking solution. An evaluation of the performance of the proposed method is presented that shows both simulated and experimental data. The IMM tracking algorithm is implemented using range, range-rate, and azimuth data from a Delphi electronically scanning radar. Results show improved navigation performance when utilizing the relative observations during GPS outages. Specifically, the drift of the INS solution is bounded by the external measurements provided by the IMM tracking filter when GPS is unavailable, maintaining the desired performance in GPS adverse conditions.},
	language = {en},
	urldate = {2024-06-20},
	author = {Selikoff, Joseph and Bevly, David M.},
	month = sep,
	year = {2018},
	pages = {1590--1604},
}

This work proposes a method of collaborative ground vehicle navigation utilizing shared radar data to provide observations during periods of GPS degradation. Navigational errors that typically arise from degraded GPS signals are reduced by providing relative observations between vehicles from an Interacting Multiple Model (IMM) radar tracking filter. Loosely coupled GPS/INS Extended Kalman Filters provide navigation solutions for each vehicle. When a vehicle experiences GPS outages, other vehicles provide external observations from the IMM tracking filter to correct the INS solution and bound error growth during the outage. The IMM tracking filter uses constant velocity, constant acceleration, and constant turn models in combination to generate a tracking solution. An evaluation of the performance of the proposed method is presented that shows both simulated and experimental data. The IMM tracking algorithm is implemented using range, range-rate, and azimuth data from a Delphi electronically scanning radar. Results show improved navigation performance when utilizing the relative observations during GPS outages. Specifically, the drift of the INS solution is bounded by the external measurements provided by the IMM tracking filter when GPS is unavailable, maintaining the desired performance in GPS adverse conditions.

@unpublished{starling_error_2017,
	title = {Error {Analysis} of {Carrier} {Phase} {Positioning} {Using} {Controlled} {Reception} {Pattern} {Antenna} {Arrays}},
	url = {https://etd.auburn.edu//handle/10415/5601},
	abstract = {This thesis analyzes and provides algorithms that protect against various carrier phase positioning errors caused by anti-jamming algorithms commonly used to position in a jamming environment. These position errors include effects from the Least-Mean-Square algorithm distorting measurements and the loss of accuracy when an anti-jamming receiver is in the presence of a jammer. While there are a number of different methods in which anti-jamming performance can be accomplished in a GPS receiver, the focus of this thesis is on algorithms that are implemented using multiple antennas, also known as controlled reception pattern array (CRPA) antennas. Carrier phase positioning is a highly accurate position solution, capable of positioning a user down to the centimeter level. However, the increased accuracy also makes the receiver susceptible to new sources of error not typically found when using the ranging code, due to the lower amount of noise on the measurement. Therefore, the effect and magnitude of these errors must be examined. 

CRPA anti-jam algorithms attenuate interference and/or strengthen desired signals by leveraging the array's spatial, temporal, and frequency difference between each of the antennas in combination with phase shifting and scaling each antenna's received signal. While this operation can remove or weaken the interference signal, algorithms such as Least-Mean-Square can have a biasing effect on a phase lock loop's estimate of the Doppler frequency due to time variant phase shift applied by the algorithm. Depending on algorithm parameters, the time variant phase shift can cause position drifts of up to a centimeter per minute. The use of a normalization process is shown as a method to remove the phase shift, and therefore the position bias, while not degrading the anti-jam performance.

The second focus of this thesis is the ability of the CRPA anti-jam receiver to maintain carrier phase position accuracy, on the order of centimeters of less, in a jamming environment. In this experiment, a four element receiver is tested with a wide range of jamming strengths and the standard deviation of Doppler measurements are averaged across all channels to provide an estimate of the accuracy of the carrier phase position solution. Because the tracking loop can be tuned to handle various amounts of noise, the phase lock loop (PLL)  bandwidth was varied and individually tested with each jamming strength. At the limits of the CRPA anti-jam receiver's nulling ability, a position solution was computed using a typical receiver PLL bandwidth, a reduced bandwidth, and an extremely low bandwidth with the aiding of an IMU. The results show that the bandwidth must be reduced significantly to maintain carrier phase position accuracy and the tracking loop must be aided by an IMU in order to obtain millimeter accuracy in the high jamming environment.},
	language = {en},
	urldate = {2024-06-25},
	author = {Starling, Joshua},
	month = apr,
	year = {2017},
	note = {Accepted: 2017-04-16T18:52:33Z},
}

This thesis analyzes and provides algorithms that protect against various carrier phase positioning errors caused by anti-jamming algorithms commonly used to position in a jamming environment. These position errors include effects from the Least-Mean-Square algorithm distorting measurements and the loss of accuracy when an anti-jamming receiver is in the presence of a jammer. While there are a number of different methods in which anti-jamming performance can be accomplished in a GPS receiver, the focus of this thesis is on algorithms that are implemented using multiple antennas, also known as controlled reception pattern array (CRPA) antennas. Carrier phase positioning is a highly accurate position solution, capable of positioning a user down to the centimeter level. However, the increased accuracy also makes the receiver susceptible to new sources of error not typically found when using the ranging code, due to the lower amount of noise on the measurement. Therefore, the effect and magnitude of these errors must be examined. CRPA anti-jam algorithms attenuate interference and/or strengthen desired signals by leveraging the array's spatial, temporal, and frequency difference between each of the antennas in combination with phase shifting and scaling each antenna's received signal. While this operation can remove or weaken the interference signal, algorithms such as Least-Mean-Square can have a biasing effect on a phase lock loop's estimate of the Doppler frequency due to time variant phase shift applied by the algorithm. Depending on algorithm parameters, the time variant phase shift can cause position drifts of up to a centimeter per minute. The use of a normalization process is shown as a method to remove the phase shift, and therefore the position bias, while not degrading the anti-jam performance. The second focus of this thesis is the ability of the CRPA anti-jam receiver to maintain carrier phase position accuracy, on the order of centimeters of less, in a jamming environment. In this experiment, a four element receiver is tested with a wide range of jamming strengths and the standard deviation of Doppler measurements are averaged across all channels to provide an estimate of the accuracy of the carrier phase position solution. Because the tracking loop can be tuned to handle various amounts of noise, the phase lock loop (PLL) bandwidth was varied and individually tested with each jamming strength. At the limits of the CRPA anti-jam receiver's nulling ability, a position solution was computed using a typical receiver PLL bandwidth, a reduced bandwidth, and an extremely low bandwidth with the aiding of an IMU. The results show that the bandwidth must be reduced significantly to maintain carrier phase position accuracy and the tracking loop must be aided by an IMU in order to obtain millimeter accuracy in the high jamming environment.

@unpublished{sherer_radar_2017,
	title = {Radar {Probabilistic} {Data} {Association} {Filter} with {GPS} {Aiding} for {Target} {Selection} and {Relative} {Position} {Determination}},
	url = {https://etd.auburn.edu//handle/10415/5686},
	abstract = {In this thesis, Global Positioning System (GPS) and radar measurements are utilized in a multi-sensor architecture to achieve a confident relative positioning solution between two vehicles. A GPS solution providing a three-dimensional positioning vector is deter- mined using pseudorange and carrier phase measurements. The carrier phase measurements make sub-meter level accuracy achievable. However, the carrier phase ambiguity must be re- solved before estimating the relative position vector. A Dynamic Base Real-Time Kinematic (DRTK) positioning algorithm using differential GPS methods is used to achieve highly precise relative positioning between the two GPS antennas. A comparison of the performance of the DRTK algorithm using either single frequency (L1 or L2 frequency only) or dual frequency (L1 and L2 frequency) measurements is introduced.

The radar measurements including range, range rate, and bearing will be utilized in a probabilistic data association filter (PDAF). The PDAF determines which of the radar channels’ solutions are considered valid, and the weighted mean of these solutions is used as the selected target measurements. The PDAF algorithm is discussed in great detail, and the performance of the PDAF algorithm using radar measurements and the performance of the DRTK solution are compared and presented demonstrating that the radar PDAF solution tracks the desired target with reasonable accuracy as long as the lead vehicle is in line of sight.

Finally, the DRTK algorithm is extended to incorporate the radar PDAF solution to increase solution availability, output rate, and reliability of the algorithm’s solution. The PDAF algorithm’s solution using the radar measurements can be utilized during GPS out- ages. The update rate of the radar measurements is ten times faster than the rate of the GPS receiver. The resultant combined system produces estimates at a much higher output rate. The integrated DRTK/PDAF system is implemented with three integration architectures including two “switch” methods and a sensor fusion Kalman filter. Analysis of the accuracy of the integrated systems is presented using experimental data collected on various test vehicles, and some conclusions can be made. The GPS measurements can assist the PDAF solution when the lead vehicle is not visible to the following vehicle. Also, the DRTK/PDAF integrated system produces a more robust relative positioning solution at a higher update rate than either sensor could produce individually.},
	language = {en},
	urldate = {2024-06-25},
	author = {Sherer, Tyler},
	month = apr,
	year = {2017},
	note = {Accepted: 2017-04-21T21:10:17Z},
}

In this thesis, Global Positioning System (GPS) and radar measurements are utilized in a multi-sensor architecture to achieve a confident relative positioning solution between two vehicles. A GPS solution providing a three-dimensional positioning vector is deter- mined using pseudorange and carrier phase measurements. The carrier phase measurements make sub-meter level accuracy achievable. However, the carrier phase ambiguity must be re- solved before estimating the relative position vector. A Dynamic Base Real-Time Kinematic (DRTK) positioning algorithm using differential GPS methods is used to achieve highly precise relative positioning between the two GPS antennas. A comparison of the performance of the DRTK algorithm using either single frequency (L1 or L2 frequency only) or dual frequency (L1 and L2 frequency) measurements is introduced. The radar measurements including range, range rate, and bearing will be utilized in a probabilistic data association filter (PDAF). The PDAF determines which of the radar channels’ solutions are considered valid, and the weighted mean of these solutions is used as the selected target measurements. The PDAF algorithm is discussed in great detail, and the performance of the PDAF algorithm using radar measurements and the performance of the DRTK solution are compared and presented demonstrating that the radar PDAF solution tracks the desired target with reasonable accuracy as long as the lead vehicle is in line of sight. Finally, the DRTK algorithm is extended to incorporate the radar PDAF solution to increase solution availability, output rate, and reliability of the algorithm’s solution. The PDAF algorithm’s solution using the radar measurements can be utilized during GPS out- ages. The update rate of the radar measurements is ten times faster than the rate of the GPS receiver. The resultant combined system produces estimates at a much higher output rate. The integrated DRTK/PDAF system is implemented with three integration architectures including two “switch” methods and a sensor fusion Kalman filter. Analysis of the accuracy of the integrated systems is presented using experimental data collected on various test vehicles, and some conclusions can be made. The GPS measurements can assist the PDAF solution when the lead vehicle is not visible to the following vehicle. Also, the DRTK/PDAF integrated system produces a more robust relative positioning solution at a higher update rate than either sensor could produce individually.

@unpublished{jantz_development_2017,
	title = {Development of a {Multi}-mode {Adaptive} {Controller} and {Investigation} of {Gain} {Variations} with {Speed} and {Balance} {Changes}},
	url = {https://etd.auburn.edu//handle/10415/5951},
	abstract = {Magnetic bearings offer a number of advantages over conventional rolling element bearings.
Magnetic bearings provide support for rotating systems through magnetic levitation rather
than by mechanical contact, nearly eliminating the energy losses attributable to friction in
standard bearings. Low power consumption is one characteristic of magnetic bearings that has
encouraged their use in an increasing number of applications. Another is the ability to use the
bearing itself as an actuator in a controller that can alter the orbit of the rotating system within
the bearing to reduce or eliminate the detrimental effects of disturbances acting on the system.
In addition, controller outputs can potentially be used as an indicator of the general health or
integrity of the system.
This work details the development of a multi-mode adaptive controller for a magnetic bearing
system that is capable of suppressing disturbances acting at synchronous and asynchronous
frequencies and caused by rotating imbalances and base motion. The work was based on an
existing adaptive controller that formed part of the overall control system for a well sorted and
well developed magnetically suspended rotor and flywheel. The development of the controller
made extensive use of system modeling techniques and model-in-the-loop simulations.
Development also required continual refinement of the system model and on-going
reconfiguration of the operating environment since the ever increasing complexity of the
controller often exceeded the real-time capabilities of the processor.
The modes of the controller, or the methods used by it to determine the frequency of the
disturbance acting on the system, include discrete Fourier transform, rotor speed and manual
observation. The adaptive controller was shown to produce excellent disturbance rejection
and vibration suppression in all of the three modes. The capabilities of the controller operating
in the first mode were demonstrated with simulated disturbances and in the second and third
modes with software simulations, simulated disturbances and physical changes in the balance
of the rotor and flywheel.
iii
This work also details the efforts to evaluate the predictive capability of adaptive controller
gains. The correlation between gain variations and balance state has been demonstrated, but a
repeatable and unambiguous response of the gains to a synchronous disturbance undetectable
by other means has not been well established. The sensitivity of the gains to variations in rotor
speed increases the difficulty of this task. Software simulations of the adaptive controller
operating in speed mode showed the potential of using the gains as an indicator of a change in
the balance or health of the system, but actual tests conducted on the magnetic bearing system
were not as encouraging.},
	language = {en},
	urldate = {2024-06-25},
	author = {Jantz, James},
	month = sep,
	year = {2017},
	note = {Accepted: 2017-09-21T20:24:17Z},
}

Magnetic bearings offer a number of advantages over conventional rolling element bearings. Magnetic bearings provide support for rotating systems through magnetic levitation rather than by mechanical contact, nearly eliminating the energy losses attributable to friction in standard bearings. Low power consumption is one characteristic of magnetic bearings that has encouraged their use in an increasing number of applications. Another is the ability to use the bearing itself as an actuator in a controller that can alter the orbit of the rotating system within the bearing to reduce or eliminate the detrimental effects of disturbances acting on the system. In addition, controller outputs can potentially be used as an indicator of the general health or integrity of the system. This work details the development of a multi-mode adaptive controller for a magnetic bearing system that is capable of suppressing disturbances acting at synchronous and asynchronous frequencies and caused by rotating imbalances and base motion. The work was based on an existing adaptive controller that formed part of the overall control system for a well sorted and well developed magnetically suspended rotor and flywheel. The development of the controller made extensive use of system modeling techniques and model-in-the-loop simulations. Development also required continual refinement of the system model and on-going reconfiguration of the operating environment since the ever increasing complexity of the controller often exceeded the real-time capabilities of the processor. The modes of the controller, or the methods used by it to determine the frequency of the disturbance acting on the system, include discrete Fourier transform, rotor speed and manual observation. The adaptive controller was shown to produce excellent disturbance rejection and vibration suppression in all of the three modes. The capabilities of the controller operating in the first mode were demonstrated with simulated disturbances and in the second and third modes with software simulations, simulated disturbances and physical changes in the balance of the rotor and flywheel. iii This work also details the efforts to evaluate the predictive capability of adaptive controller gains. The correlation between gain variations and balance state has been demonstrated, but a repeatable and unambiguous response of the gains to a synchronous disturbance undetectable by other means has not been well established. The sensitivity of the gains to variations in rotor speed increases the difficulty of this task. Software simulations of the adaptive controller operating in speed mode showed the potential of using the gains as an indicator of a change in the balance or health of the system, but actual tests conducted on the magnetic bearing system were not as encouraging.

@unpublished{humphreys_computational_2017,
	title = {A {Computational} {Fluid} {Dynamics} {Analysis} of a {Driver}-{Assistive} {Truck} {Platooning} {System} with {Lateral} {Offset}},
	url = {https://etd.auburn.edu//handle/10415/5624},
	abstract = {This study utilizes Computational Fluid Dynamics to analyze the aerodynamic drag performance of a two-truck Driver-Assistive Truck Platooning system. Simulations were conducted to characterize the drag reduction versus separation distance trend for standard platooning from separation distances from 0-100 ft. From the CFD simulations, it was determined that the drag reduction monotonically increased as the separation distance diminished. Fuel economy tests were then conducted to compare the simulated results to practical experimental results. The follower truck’s fuel economy improvement differed from the CFD predictions, and thus a new series of simulations were conducted to determine the impact of external platooning effects such as lateral offset and crosswind. These results were then compared to both the original CFD simulations, as well as fuel economy results and select wind tunnel results from various other groups. The CFD simulations of lateral offset demonstrated a significant degradation in the follower truck’s savings, whilst the lead truck was mostly unaffected. CFD simulations also predict that crosswind also degrades the centered drag reduction trend for both vehicles, while also accentuating the degradation present in the lateral offset trends. This reduction in aerodynamic drag savings is also predicted to be directionally dependent for the lateral offset cases.},
	language = {en},
	urldate = {2024-06-25},
	author = {Humphreys, Hugh},
	month = apr,
	year = {2017},
	note = {Accepted: 2017-04-17T20:58:42Z},
}

This study utilizes Computational Fluid Dynamics to analyze the aerodynamic drag performance of a two-truck Driver-Assistive Truck Platooning system. Simulations were conducted to characterize the drag reduction versus separation distance trend for standard platooning from separation distances from 0-100 ft. From the CFD simulations, it was determined that the drag reduction monotonically increased as the separation distance diminished. Fuel economy tests were then conducted to compare the simulated results to practical experimental results. The follower truck’s fuel economy improvement differed from the CFD predictions, and thus a new series of simulations were conducted to determine the impact of external platooning effects such as lateral offset and crosswind. These results were then compared to both the original CFD simulations, as well as fuel economy results and select wind tunnel results from various other groups. The CFD simulations of lateral offset demonstrated a significant degradation in the follower truck’s savings, whilst the lead truck was mostly unaffected. CFD simulations also predict that crosswind also degrades the centered drag reduction trend for both vehicles, while also accentuating the degradation present in the lateral offset trends. This reduction in aerodynamic drag savings is also predicted to be directionally dependent for the lateral offset cases.

@unpublished{park_reduced_2017,
	title = {A {Reduced} {Element} {Map} {Representation} and {Applications}: {Map} {Merging}, {Path} {Planning}, and {Target} {Interception}},
	shorttitle = {A {Reduced} {Element} {Map} {Representation} and {Applications}},
	url = {https://etd.auburn.edu//handle/10415/5849},
	abstract = {Modern autonomous systems require complex and heavy computations. The complexity can be reduced by eliminating or integrating redundant information. In the case of mobile vehicles, occupancy grid map representations are conventionally adopted for path planning. Based on a grid map, a reduced element map representation named a rectangular map or an R-map has been introduced. The concept of R-map is integration of empty elements of a grid map into fewer elements with maximal sizes. Since an R-map has a reduced number of elements, path planning computations become much faster than conventional maps. Also, because the R-map algorithm focuses only on free space, it is naturally suited for obstacle avoidance. 

The R-map can also be applied to map merging problems. Since R-maps represent spaces with varied sizes of rectangles, this feature can be a good source to recognize certain locations on the maps, unlike regular gridded cells. This work accomplishes map merging of local maps with unknown factors in their orientations, accuracy, and scales using the rectangular features from the R-map.

Further, this study extends the concept of the 2D R-map to 3D environments. Since 3D environments have an additional dimension of the z-axis, the process of R-mapping will be slightly different from 2D R-mapping, and the integrated cells will be represented as cuboids (volumes) instead of rectangles (areas). Those maximal empty cuboids (MECs) are obstacle-free spaces, and autonomous vehicles can accomplish obstacle avoidance by moving through a sequence of MECs. As applications, algorithms for path planning on R-maps are provided for stationary- and maneuvering-target interception in cluttered environments. This approach expects to provide a computational efficiency to guidance and navigation problems of autonomous systems.},
	language = {en},
	urldate = {2024-06-25},
	author = {Park, Jinyoung},
	month = jul,
	year = {2017},
	note = {Accepted: 2017-07-25T21:53:14Z},
}

Modern autonomous systems require complex and heavy computations. The complexity can be reduced by eliminating or integrating redundant information. In the case of mobile vehicles, occupancy grid map representations are conventionally adopted for path planning. Based on a grid map, a reduced element map representation named a rectangular map or an R-map has been introduced. The concept of R-map is integration of empty elements of a grid map into fewer elements with maximal sizes. Since an R-map has a reduced number of elements, path planning computations become much faster than conventional maps. Also, because the R-map algorithm focuses only on free space, it is naturally suited for obstacle avoidance. The R-map can also be applied to map merging problems. Since R-maps represent spaces with varied sizes of rectangles, this feature can be a good source to recognize certain locations on the maps, unlike regular gridded cells. This work accomplishes map merging of local maps with unknown factors in their orientations, accuracy, and scales using the rectangular features from the R-map. Further, this study extends the concept of the 2D R-map to 3D environments. Since 3D environments have an additional dimension of the z-axis, the process of R-mapping will be slightly different from 2D R-mapping, and the integrated cells will be represented as cuboids (volumes) instead of rectangles (areas). Those maximal empty cuboids (MECs) are obstacle-free spaces, and autonomous vehicles can accomplish obstacle avoidance by moving through a sequence of MECs. As applications, algorithms for path planning on R-maps are provided for stationary- and maneuvering-target interception in cluttered environments. This approach expects to provide a computational efficiency to guidance and navigation problems of autonomous systems.

@unpublished{martin_gps_2017,
	title = {{GPS} {Carrier} {Phase} {Tracking} in {Difficult} {Environments} {Using} {Vector} {Tracking} {For} {Precise} {Positioning} and {Vehicle} {Attitude} {Estimation}},
	url = {https://etd.auburn.edu//handle/10415/5692},
	abstract = {In this dissertation, two approaches are developed to improve the carrier phase tracking performance of a software-defined GPS receiver. The first approach combines a non-coherent vector tracking architecture with a local phase locked loop to improve carrier phase tracking performance of a stand-alone (i.e. not base station) GPS receiver. The Vector Frequency Locked Loop (VFLL) aided Phase Locked Loop (PLL) receiver is shown to provide a more robust carrier phase tracking performance at low carrier-to-noise density (C/N\$\_0\$) ratios. The VFLL aided PLL is able to maintain phase lock of signal with 2 to 3 dB lower C/N\$\_0\$ ratio. The more significant improvement is that, while the scalar tracking receiver quickly lost phase lock completely at low C/N\$\_0\$ ratios, the VFLL aided PLL only slipped cycles.

The second approach is designed to include measurements from a local base station. The Real-Time Kinematic (RTK) vector phase locked loop receiver is derived. The RTK VPLL receiver is a true carrier phase tracking receiver in that the navigation filter is updated using correlator outputs, and there is no local loop filter for each tracking channel. The tracking loop is closed by predicting the received carrier phase using the navigation solution. Base station measurements are combined with relative position vector estimates from the navigation filter and fixed carrier ambiguities to close the tracking loops. In simulation, the RTK VPLL maintains phase lock at C/N\$\_0\$ ratios 4 to 8 dB lower than a traditional scalar tracking receiver. During experimental testing, the RTK VPLL receiver maintains the navigation solution and carrier phase tracking throughout tests in moderate and heavy foliage. There are times during the experimental test that the RTK VPLL receiver slipped cycles of the carrier, and the navigation solution degrades as a result. The environment prevents the standard receiver from reporting a high precision solution for even longer periods.  

Finally, the benefits of the RTK VPLL receiver design are investigated in a multi-antenna configuration. Data from multiple GPS antennas mounted on a rigid body may be used to estimate the attitude of the platform. The solution for finding the three Euler angles (i.e. roll, pitch, and yaw) of the platform given two relative position vectors is provided. Two studies are performed to identify possible improvements to the software receiver design developed in this dissertation. A modified two antenna RTK VPLL algorithm was developed and tested in simulation. It is shown that the two antenna algorithm does not significantly improve the carrier phase tracking performance at low C/N\$\_0\$ ratios. An RTK carrier ambiguity estimation procedure is developed using the multiple antenna configuration and the known antenna separation distance. The new baseline constrained ambiguity estimation algorithm significantly reduces time to fix and provide a method for rejecting incorrect fixes.},
	language = {en},
	urldate = {2024-06-25},
	author = {Martin, Scott},
	month = apr,
	year = {2017},
	note = {Accepted: 2017-04-25T15:47:40Z},
}

In this dissertation, two approaches are developed to improve the carrier phase tracking performance of a software-defined GPS receiver. The first approach combines a non-coherent vector tracking architecture with a local phase locked loop to improve carrier phase tracking performance of a stand-alone (i.e. not base station) GPS receiver. The Vector Frequency Locked Loop (VFLL) aided Phase Locked Loop (PLL) receiver is shown to provide a more robust carrier phase tracking performance at low carrier-to-noise density (C/N$_0$) ratios. The VFLL aided PLL is able to maintain phase lock of signal with 2 to 3 dB lower C/N$_0$ ratio. The more significant improvement is that, while the scalar tracking receiver quickly lost phase lock completely at low C/N$_0$ ratios, the VFLL aided PLL only slipped cycles. The second approach is designed to include measurements from a local base station. The Real-Time Kinematic (RTK) vector phase locked loop receiver is derived. The RTK VPLL receiver is a true carrier phase tracking receiver in that the navigation filter is updated using correlator outputs, and there is no local loop filter for each tracking channel. The tracking loop is closed by predicting the received carrier phase using the navigation solution. Base station measurements are combined with relative position vector estimates from the navigation filter and fixed carrier ambiguities to close the tracking loops. In simulation, the RTK VPLL maintains phase lock at C/N$_0$ ratios 4 to 8 dB lower than a traditional scalar tracking receiver. During experimental testing, the RTK VPLL receiver maintains the navigation solution and carrier phase tracking throughout tests in moderate and heavy foliage. There are times during the experimental test that the RTK VPLL receiver slipped cycles of the carrier, and the navigation solution degrades as a result. The environment prevents the standard receiver from reporting a high precision solution for even longer periods. Finally, the benefits of the RTK VPLL receiver design are investigated in a multi-antenna configuration. Data from multiple GPS antennas mounted on a rigid body may be used to estimate the attitude of the platform. The solution for finding the three Euler angles (i.e. roll, pitch, and yaw) of the platform given two relative position vectors is provided. Two studies are performed to identify possible improvements to the software receiver design developed in this dissertation. A modified two antenna RTK VPLL algorithm was developed and tested in simulation. It is shown that the two antenna algorithm does not significantly improve the carrier phase tracking performance at low C/N$_0$ ratios. An RTK carrier ambiguity estimation procedure is developed using the multiple antenna configuration and the known antenna separation distance. The new baseline constrained ambiguity estimation algorithm significantly reduces time to fix and provide a method for rejecting incorrect fixes.

@unpublished{gurley_enabling_2017,
	title = {Enabling {Shape} {Memory} {Alloys} as {Actuators} for {Robotics}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/6000},
	abstract = {Does any existing technology provide a viable actuator for the high degree-of-freedom robots that will soon be ubiquitous in society? If a technology exists that is in any way superior to the electric motor for robotics – why has it not come into common use? What are the technology’s benefits and flaws, and can these flaws be overcome? This thesis seeks to answer these questions. The author believes that, of all known devices which convert electrical energy to mechanical motion, shape memory alloy actuators provide the most convincing capabilities to fulfill the needs of complex robots over the next decades. The electro-magnetic motor has moved industry and automation for over a century, yet modern robotic machines are reaching the fundamental limits of its ability as mechanical systems increase in complexity while decreasing in size. Shape Memory Alloy (SMA) actuators have benefits of extraordinary high strength, high energy density, simplicity, and low cost. These benefits come along with obstacles of complex thermo-electro-mechanical behavior, difficult control, fatigue over time, and moderate speed – all of which can be overcome – as well as barriers of low energy efficiency and limited life-time which cannot be overcome. This thesis addresses all of the obstacles to enable more powerful and capable robots, answering the essential question: How can we enable SMA technology so that it becomes useful for robotics?},
	language = {en},
	urldate = {2024-06-25},
	author = {Gurley, Austin},
	month = nov,
	year = {2017},
	note = {Accepted: 2017-11-27T20:14:25Z},
}

Does any existing technology provide a viable actuator for the high degree-of-freedom robots that will soon be ubiquitous in society? If a technology exists that is in any way superior to the electric motor for robotics – why has it not come into common use? What are the technology’s benefits and flaws, and can these flaws be overcome? This thesis seeks to answer these questions. The author believes that, of all known devices which convert electrical energy to mechanical motion, shape memory alloy actuators provide the most convincing capabilities to fulfill the needs of complex robots over the next decades. The electro-magnetic motor has moved industry and automation for over a century, yet modern robotic machines are reaching the fundamental limits of its ability as mechanical systems increase in complexity while decreasing in size. Shape Memory Alloy (SMA) actuators have benefits of extraordinary high strength, high energy density, simplicity, and low cost. These benefits come along with obstacles of complex thermo-electro-mechanical behavior, difficult control, fatigue over time, and moderate speed – all of which can be overcome – as well as barriers of low energy efficiency and limited life-time which cannot be overcome. This thesis addresses all of the obstacles to enable more powerful and capable robots, answering the essential question: How can we enable SMA technology so that it becomes useful for robotics?

@unpublished{rose_real-time_2017,
	title = {A {Real}-time {Implementation} of {Rendering} {Light} {Field} {Imagery} for {Generating} {Point} {Clouds} in {Vision} {Navigation}},
	url = {https://etd.auburn.edu//handle/10415/6059},
	abstract = {This dissertation develops a real-time implementation of rendering perspective and refocused imagery from a light field camera for the generation of sparse point clouds using a traditional stereo camera approach, a multiperspective approach, and two refocused ranging approaches.  Unlike monocular cameras that have difficulty in extracting depth information without prior knowledge of a scene either in the form of previous images or object recognition, light field, or plenoptic, cameras can estimate depth with the introduction of additional hardware in the form of a microlens array to capture the 4-D radiance.  The centers of these microlens are extracted with a calibration procedure and are used to build the radiance that contains the additional angular information that gives the plenoptic camera its ability to render multiple perspectives with a single main lens, thus improving upon the stereo or multiple camera setups that require more space and power as well as additional hardware for triggering synchronous images.  This additional information for rendering multiple perspectives and refocused images greatly increases the plenoptic image size and thus the image processing time.  With the end of dramatic growth in single processor performance, parallel processing has become the dominant method to decrease computing times.  In response, this dissertation develops efficient methods for plenoptic image rendering algorithms for single core processor, multiple core processor, and graphics processing unit (GPU) architectures.

The multiple core processor architecture is realized through OpenMP with an Intel Core i7-4720HQ processor, and the GPU implementation uses Nvidia's CUDA API with a GeForce GTX 980M.  For the perspective image rendering from the plenoptic case, OpenMP gives a 3.9x speedup from 21.8 ms with a single core to 5.6 ms on eight cores.  The integral refocused image case improves its computation time with OpenMP from 699 ms for the serial architecture to 242.1 ms with eight cores for a 2.9x speedup.  A 3.3x speedup is achieved with OpenMP for the FFT refocused imaging case from 717.3 ms for one core to 217.4 ms using eight cores.  The perspective image rendering from the plenoptic image case has a GPU computation time of 5.6 ms and a speedup of 3.9x over the single core processing time.  Computation with CUDA takes 17.3 ms to render an integral refocused image which amounts to a 40x speedup over the single core processing time.  Finally, the FFT refocused imaging case results in a 14.6x speedup over the serial time with a total computation time of 49 ms.

Four methods are discussed in this dissertation for determining range using these efficiently rendered multiple perspective and refocused images: stereo ranging, multiperspective ranging, integral refocused ranging, and FFT refocused ranging.  The stereo ranging approach follows similar techniques as traditional stereo algorithms through the ability of the plenoptic camera to render two virtual cameras.  A multiperspective ranging approach uses an extrinsic property calibration model to rectify multiple virtual stereo pairs for a robust multiple stereo-pair ranging approach.  Two depth-from-focus approaches use correlation to measure the depth through either an integral-based refocusing method or an FFT-based refocusing method to compare the alpha-refocused image with the in-focus perspective image.  A ranging model then relates the alpha at the maximum correlation with the distance.  During experimental testing, each of the four ranging algorithms estimates ranges to tracked features on a target using a 55 mm lens and a 135 mm lens.  The 55 mm lens renders images with a field of view of 40 degrees at the cost of a maximum range of about 2 meters, while the 135 mm lens estimates improved ranges out to 6.5 meters at the cost of a field of view of only 16 degrees.  Finally, this dissertation demonstrates plenoptic odometry with target tracking using each of the four ranging methods.},
	language = {en},
	urldate = {2024-06-25},
	author = {Rose, Christopher},
	month = dec,
	year = {2017},
	note = {Accepted: 2017-12-11T14:15:07Z},
}

This dissertation develops a real-time implementation of rendering perspective and refocused imagery from a light field camera for the generation of sparse point clouds using a traditional stereo camera approach, a multiperspective approach, and two refocused ranging approaches. Unlike monocular cameras that have difficulty in extracting depth information without prior knowledge of a scene either in the form of previous images or object recognition, light field, or plenoptic, cameras can estimate depth with the introduction of additional hardware in the form of a microlens array to capture the 4-D radiance. The centers of these microlens are extracted with a calibration procedure and are used to build the radiance that contains the additional angular information that gives the plenoptic camera its ability to render multiple perspectives with a single main lens, thus improving upon the stereo or multiple camera setups that require more space and power as well as additional hardware for triggering synchronous images. This additional information for rendering multiple perspectives and refocused images greatly increases the plenoptic image size and thus the image processing time. With the end of dramatic growth in single processor performance, parallel processing has become the dominant method to decrease computing times. In response, this dissertation develops efficient methods for plenoptic image rendering algorithms for single core processor, multiple core processor, and graphics processing unit (GPU) architectures. The multiple core processor architecture is realized through OpenMP with an Intel Core i7-4720HQ processor, and the GPU implementation uses Nvidia's CUDA API with a GeForce GTX 980M. For the perspective image rendering from the plenoptic case, OpenMP gives a 3.9x speedup from 21.8 ms with a single core to 5.6 ms on eight cores. The integral refocused image case improves its computation time with OpenMP from 699 ms for the serial architecture to 242.1 ms with eight cores for a 2.9x speedup. A 3.3x speedup is achieved with OpenMP for the FFT refocused imaging case from 717.3 ms for one core to 217.4 ms using eight cores. The perspective image rendering from the plenoptic image case has a GPU computation time of 5.6 ms and a speedup of 3.9x over the single core processing time. Computation with CUDA takes 17.3 ms to render an integral refocused image which amounts to a 40x speedup over the single core processing time. Finally, the FFT refocused imaging case results in a 14.6x speedup over the serial time with a total computation time of 49 ms. Four methods are discussed in this dissertation for determining range using these efficiently rendered multiple perspective and refocused images: stereo ranging, multiperspective ranging, integral refocused ranging, and FFT refocused ranging. The stereo ranging approach follows similar techniques as traditional stereo algorithms through the ability of the plenoptic camera to render two virtual cameras. A multiperspective ranging approach uses an extrinsic property calibration model to rectify multiple virtual stereo pairs for a robust multiple stereo-pair ranging approach. Two depth-from-focus approaches use correlation to measure the depth through either an integral-based refocusing method or an FFT-based refocusing method to compare the alpha-refocused image with the in-focus perspective image. A ranging model then relates the alpha at the maximum correlation with the distance. During experimental testing, each of the four ranging algorithms estimates ranges to tracked features on a target using a 55 mm lens and a 135 mm lens. The 55 mm lens renders images with a field of view of 40 degrees at the cost of a maximum range of about 2 meters, while the 135 mm lens estimates improved ranges out to 6.5 meters at the cost of a field of view of only 16 degrees. Finally, this dissertation demonstrates plenoptic odometry with target tracking using each of the four ranging methods.

@inproceedings{nelson_anvel_2017,
	title = {{ANVEL} {HIL}/{SIL} {ADDITIONS} {FOR} {NAVIGATION} {ALGORITHM} {DEVELOPMENT}},
	abstract = {This work presents the development of a high fidelity Simulation In the Loop/Hardware In the Loop simulation environment using add-ons to Autonomous Navigation Virtual Environment Laboratory (ANVEL) and a navigation unit developed by Auburn University’s GPS and Vehicle Dynamics Lab (GAVLAB) in support of the United States Army’s Autonomous Ground Resupply Science Technology Objective. The developed add-ons include a real time interface for ANVEL, Inertial Measurement Unit module, Wheel Speed Sensor module, and a GPS module that allows simulated signals or generated Radio Frequency signals. The developed add-ons allow for faster development of navigation algorithms and controllers due to a readily available, highly accurate truth from ANVEL and can be configured to introduce realistic errors from sensors, hardware, and GPS signals such that algorithm and controller robustness can be easily examined.},
	language = {en},
	author = {Nelson, Brently and Bevly, David and Ratowski, Jeff and Theisen, Bernard},
	year = {2017},
}

This work presents the development of a high fidelity Simulation In the Loop/Hardware In the Loop simulation environment using add-ons to Autonomous Navigation Virtual Environment Laboratory (ANVEL) and a navigation unit developed by Auburn University’s GPS and Vehicle Dynamics Lab (GAVLAB) in support of the United States Army’s Autonomous Ground Resupply Science Technology Objective. The developed add-ons include a real time interface for ANVEL, Inertial Measurement Unit module, Wheel Speed Sensor module, and a GPS module that allows simulated signals or generated Radio Frequency signals. The developed add-ons allow for faster development of navigation algorithms and controllers due to a readily available, highly accurate truth from ANVEL and can be configured to introduce realistic errors from sensors, hardware, and GPS signals such that algorithm and controller robustness can be easily examined.

@article{bishop_evaluation_2017,
	title = {Evaluation and {Testing} of {Driver}-{Assistive} {Truck} {Platooning}: {Phase} 2 {Final} {Results}},
	volume = {2615},
	issn = {0361-1981, 2169-4052},
	shorttitle = {Evaluation and {Testing} of {Driver}-{Assistive} {Truck} {Platooning}},
	url = {http://journals.sagepub.com/doi/10.3141/2615-02},
	doi = {10.3141/2615-02},
	abstract = {Phase 2 final results are described for the FHWA Exploratory Advanced Research project titled Heavy Truck Cooperative Adaptive Cruise Control: Evaluation, Testing, and Stakeholder Engagement for Near Term Deployment, which evaluates the commercial feasibility of driver-assistive truck platooning (DATP). The project was led by Auburn University, in partnership with Peloton Technology, Peterbilt Trucks, Meritor WABCO, and the American Transportation Research Institute. DATP is a form of cooperative adaptive cruise control for heavy trucks (two-truck platoons). It takes advantage of the increasing maturity of vehicle-to-vehicle (V2V) communications (and the expected widespread deployment of V2V connectivity based on dedicated short-range communications over the next decade) to improve freight efficiency, fleet efficiency, safety, and highway mobility as well as reduce emissions. Notably, truck fleets can implement DATP regardless of the regulatory timeline for dedicated short-range communications. The Phase 2 analysis built on Phase 1 and included a testing program of a DATP prototype (with detailed SAE Type 2 fuel economy testing), wireless communications optimization, traffic modeling to understand the impact on roadways at various levels of market penetration, and additional analysis of methods to find DATP partners as well as aerodynamic simulations to understand drag on the vehicles. Detailed analysis of the fuel economy testing data is provided.},
	language = {en},
	number = {1},
	urldate = {2024-06-20},
	journal = {Transportation Research Record: Journal of the Transportation Research Board},
	author = {Bishop, Richard and Bevly, David and Humphreys, Luke and Boyd, Stephen and Murray, Daniel},
	month = jan,
	year = {2017},
	pages = {11--18},
}

Phase 2 final results are described for the FHWA Exploratory Advanced Research project titled Heavy Truck Cooperative Adaptive Cruise Control: Evaluation, Testing, and Stakeholder Engagement for Near Term Deployment, which evaluates the commercial feasibility of driver-assistive truck platooning (DATP). The project was led by Auburn University, in partnership with Peloton Technology, Peterbilt Trucks, Meritor WABCO, and the American Transportation Research Institute. DATP is a form of cooperative adaptive cruise control for heavy trucks (two-truck platoons). It takes advantage of the increasing maturity of vehicle-to-vehicle (V2V) communications (and the expected widespread deployment of V2V connectivity based on dedicated short-range communications over the next decade) to improve freight efficiency, fleet efficiency, safety, and highway mobility as well as reduce emissions. Notably, truck fleets can implement DATP regardless of the regulatory timeline for dedicated short-range communications. The Phase 2 analysis built on Phase 1 and included a testing program of a DATP prototype (with detailed SAE Type 2 fuel economy testing), wireless communications optimization, traffic modeling to understand the impact on roadways at various levels of market penetration, and additional analysis of methods to find DATP partners as well as aerodynamic simulations to understand drag on the vehicles. Detailed analysis of the fuel economy testing data is provided.

@inproceedings{martin_performance_2017,
	address = {Honolulu, Hawaii},
	title = {Performance {Analysis} of a {RTK} {Vector} {Phase} {Locked} {Loop} {Architecture} in {Degraded} {Environments}},
	url = {https://www.ion.org/publications/abstract.cfm?articleID=15037},
	doi = {10.33012/2017.15037},
	urldate = {2024-06-20},
	author = {Martin, Scott M. and Bevly, David M.},
	month = jun,
	year = {2017},
	pages = {383--397},
}

@inproceedings{pierce_opportunistic_2017,
	title = {Opportunistic {Landmark} {Registration} for {Long} {Distance} {Relative} {Path} {Following}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=15222},
	doi = {10.33012/2017.15222},
	abstract = {A method for long distance path duplication of unmanned ground vehicles using relative position information is presented. The path generation errors that typically accumulate for long distance following scenarios are mitigated by exchanging landmark observations between vehicles. Two main differential GPS techniques are used in the presented approach: Dynamic Base RTK and Time Differenced Carrier Phase. The resulting GPS measurements and landmark observations are fused in a graph-based estimation framework for long distance path duplication. The graph-based formulation reduces implementation complexity and processing requirement. A detailed performance evaluation is presented that shows results from both simulated and experimental data. The landmark registration scheme is implemented using point cloud data from a Velodyne VLP-16 multi-channel LiDAR. Results show improved performance when incorporating landmark observations and that path following errors are bounded with respect to following distance between vehicles. The results also indicate that a low number of landmarks need to be exchanged to achieve the desired performance.},
	language = {en},
	urldate = {2024-06-20},
	author = {Pierce, Dan and Martin, Scott and Bevly, David M.},
	month = sep,
	year = {2017},
	pages = {2560--2573},
}

A method for long distance path duplication of unmanned ground vehicles using relative position information is presented. The path generation errors that typically accumulate for long distance following scenarios are mitigated by exchanging landmark observations between vehicles. Two main differential GPS techniques are used in the presented approach: Dynamic Base RTK and Time Differenced Carrier Phase. The resulting GPS measurements and landmark observations are fused in a graph-based estimation framework for long distance path duplication. The graph-based formulation reduces implementation complexity and processing requirement. A detailed performance evaluation is presented that shows results from both simulated and experimental data. The landmark registration scheme is implemented using point cloud data from a Velodyne VLP-16 multi-channel LiDAR. Results show improved performance when incorporating landmark observations and that path following errors are bounded with respect to following distance between vehicles. The results also indicate that a low number of landmarks need to be exchanged to achieve the desired performance.

@inproceedings{starling_error_2017,
	title = {Error {Analysis} of {Carrier} {Phase} {Positioning} {Using} {Controlled} {Reception} {Pattern} {Array} {Antennas}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=14960},
	doi = {10.33012/2017.14960},
	abstract = {High precision GPS applications are becoming increasingly wide spread during a time where the possibility for jamming GPS has never been higher. Though there are many types of anti-jam (AJ) techniques, multiple antenna techniques provide a robust protection method during jamming environments using Spatial Adaptive Processing (SAP), Space Time Adaptive Processing (STAP), and Space Frequency Adaptive Processing (SFAP) algorithms. A multi-antenna, also known as controlled reception pattern array (CRPA), receiver provides AJ protection by changing the effective gain pattern of the array to null out the jammer signal while still tracking GPS satellites. These CRPA receivers do this by leveraging the spatial, temporal, and frequency differences of signals between each antenna of the receiver to cause constructive and destructive interference when each antenna’s signal is combined. This paper aims to evaluate and quantify the integrity of multi-antenna carrier phase positioning during jamming scenarios as well as remove or limit the sources of error. The primary focus of error in this paper is the error associated with unconstrained recursive algorithms that continuously phase shift the reference element as well as the error in the carrier phase position solution when an AJ algorithm at various jammer strength levels.},
	language = {en},
	urldate = {2024-06-20},
	author = {Starling, Joshua and Bevly, David M.},
	month = feb,
	year = {2017},
	pages = {957--970},
}

High precision GPS applications are becoming increasingly wide spread during a time where the possibility for jamming GPS has never been higher. Though there are many types of anti-jam (AJ) techniques, multiple antenna techniques provide a robust protection method during jamming environments using Spatial Adaptive Processing (SAP), Space Time Adaptive Processing (STAP), and Space Frequency Adaptive Processing (SFAP) algorithms. A multi-antenna, also known as controlled reception pattern array (CRPA), receiver provides AJ protection by changing the effective gain pattern of the array to null out the jammer signal while still tracking GPS satellites. These CRPA receivers do this by leveraging the spatial, temporal, and frequency differences of signals between each antenna of the receiver to cause constructive and destructive interference when each antenna’s signal is combined. This paper aims to evaluate and quantify the integrity of multi-antenna carrier phase positioning during jamming scenarios as well as remove or limit the sources of error. The primary focus of error in this paper is the error associated with unconstrained recursive algorithms that continuously phase shift the reference element as well as the error in the carrier phase position solution when an AJ algorithm at various jammer strength levels.

@inproceedings{sherer_keynote_2017,
	title = {Keynote: {Radar} {Probabilistic} {Data} {Association} {Filter} with {GPS} {Aiding} for {Target} {Selection} and {Relative} {Position} {Determination}},
	shorttitle = {Keynote},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=15069},
	doi = {10.33012/2017.15069},
	abstract = {As navigation systems are being developed, it is apparent that accurate and precise positioning is an imperative for both military and civilian ground vehicle guidance. There is also a significant desire for cost-effective navigation systems that civilians can afford. As the need for this technology increases, navigation systems incorporating multiple sensors have been developed and relied upon in many navigation situations. In this work, radar and GPS measurements are utilized in a multisensor fusion scheme that allows for a robust ranging solution utilizing the accuracy of a DGPS solution and the higher update rate of the radar solution in a Kalman filter. One difficulty when navigating with radar is the problem of target selection, which is the determination of the correct channel of the radar that is tracking the desired target. To accomplish this task, a probabilistic data association filter (PDAF) is utilized to determine a weighted mean of the channels’ solutions that fall within a validation region set in the algorithm. This paper intends to evaluate and make conclusions on the performance of a GPS/Radar fusion algorithm in various vehicle convoying scenarios.},
	language = {en},
	urldate = {2024-06-20},
	author = {Sherer, Tyler P. and Martin, Scott M. and Bevly, David M.},
	month = may,
	year = {2017},
	pages = {419--428},
}

As navigation systems are being developed, it is apparent that accurate and precise positioning is an imperative for both military and civilian ground vehicle guidance. There is also a significant desire for cost-effective navigation systems that civilians can afford. As the need for this technology increases, navigation systems incorporating multiple sensors have been developed and relied upon in many navigation situations. In this work, radar and GPS measurements are utilized in a multisensor fusion scheme that allows for a robust ranging solution utilizing the accuracy of a DGPS solution and the higher update rate of the radar solution in a Kalman filter. One difficulty when navigating with radar is the problem of target selection, which is the determination of the correct channel of the radar that is tracking the desired target. To accomplish this task, a probabilistic data association filter (PDAF) is utilized to determine a weighted mean of the channels’ solutions that fall within a validation region set in the algorithm. This paper intends to evaluate and make conclusions on the performance of a GPS/Radar fusion algorithm in various vehicle convoying scenarios.

@inproceedings{powell_multiple-antenna_2017,
	title = {A {Multiple}-{Antenna} {Software} {GPS} {Signal} {Simulator} for {Rapid} {Testing} of {Interference} {Mitigation} {Techniques}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=14922},
	doi = {10.33012/2017.14922},
	abstract = {This paper details the design of a software GPS signal simulator and illustrates how it can be used to support rapid testing of GPS interference mitigation research. The MATLAB-based signal simulator is capable of generating digital GPS signals at intermediate frequencies (IF) for multiple-element, controlled-radiation-pattern-antenna (CRPA) configurations in jamming environments. The simulator was developed to support novel GPS interference mitigation research and analysis conducted in the GPS and Vehicle Dynamics Laboratory (GAVLAB) at Auburn University. The digital signals can be analyzed with software acquisition, tracking, and positioning techniques or can be converted to analog signals at the GPS radio frequencies and played to multiple receivers via cabling using the Universal Software Radio Peripheral (USRP) software-defined-radio (SDR) platform. A GPS IF-signal for a single antenna generated by the software simulator was played-back and recorded simultaneously with USRPs and compared to an IF-signal for the same scenario generated by a hardware GPS signal simulator which was also recorded with a USRP. Position and velocity measurements calculated by a software receiver from the simulated IF signal, the played-back and recorded IF signal, and the signal generated by the hardware simulator are compared to evaluate the baseline performance of the software simulator. Results of this experiment illustrate that a software simulator paired with the USRP is comparable in performance to the hardware simulator for single antenna applications. A four-element CRPA interference simulation was generated by the software simulator and analyzed with a software receiver that was modified to include multi-antenna interference mitigation techniques. Results provided from the CRPA simulation by the modified software receiver illustrate that a software GPS simulator is a powerful tool for rapid development of GPS interference mitigation techniques in the software domain. Lastly, the simulated CRPA signals were played-back and recorded simultaneously with multiple USRPs to examine the feasibility of using relatively inexpensive SDRs to simulate multiple-antenna GPS scenarios. Results from this test illustrate that a multiple-USRP setup is a useful tool for testing robust interference mitigation techniques.},
	language = {en},
	urldate = {2024-06-20},
	author = {Powell, Russell and Starling, Joshua and Bevly, David},
	month = feb,
	year = {2017},
	pages = {714--729},
}

This paper details the design of a software GPS signal simulator and illustrates how it can be used to support rapid testing of GPS interference mitigation research. The MATLAB-based signal simulator is capable of generating digital GPS signals at intermediate frequencies (IF) for multiple-element, controlled-radiation-pattern-antenna (CRPA) configurations in jamming environments. The simulator was developed to support novel GPS interference mitigation research and analysis conducted in the GPS and Vehicle Dynamics Laboratory (GAVLAB) at Auburn University. The digital signals can be analyzed with software acquisition, tracking, and positioning techniques or can be converted to analog signals at the GPS radio frequencies and played to multiple receivers via cabling using the Universal Software Radio Peripheral (USRP) software-defined-radio (SDR) platform. A GPS IF-signal for a single antenna generated by the software simulator was played-back and recorded simultaneously with USRPs and compared to an IF-signal for the same scenario generated by a hardware GPS signal simulator which was also recorded with a USRP. Position and velocity measurements calculated by a software receiver from the simulated IF signal, the played-back and recorded IF signal, and the signal generated by the hardware simulator are compared to evaluate the baseline performance of the software simulator. Results of this experiment illustrate that a software simulator paired with the USRP is comparable in performance to the hardware simulator for single antenna applications. A four-element CRPA interference simulation was generated by the software simulator and analyzed with a software receiver that was modified to include multi-antenna interference mitigation techniques. Results provided from the CRPA simulation by the modified software receiver illustrate that a software GPS simulator is a powerful tool for rapid development of GPS interference mitigation techniques in the software domain. Lastly, the simulated CRPA signals were played-back and recorded simultaneously with multiple USRPs to examine the feasibility of using relatively inexpensive SDRs to simulate multiple-antenna GPS scenarios. Results from this test illustrate that a multiple-USRP setup is a useful tool for testing robust interference mitigation techniques.

@unpublished{robertson_design_2016,
	title = {Design of a {Guidance} {Controller} {Using} {Network} {Topology}},
	url = {https://etd.auburn.edu//handle/10415/5392},
	abstract = {In dynamic environments, the control of a formation of unmanned vehicles remains a significant control problem on both network and guidance dynamics levels. Currently, formations of unmanned vehicles require multiple ground operators to supervise the movement of a formation to effectively execute a task or mission objective. By designating a single vehicle as the lead agent of the formation, control over the entire formation reduces to a distribution of information through a single vehicle, thereby reducing the number of required ground operators. In such architectures, the location of the leader and the manner in which the control is distributed amongst the decentralized formation must suit the desired behavior requested by the ground operator. This work centers on the implementation of a single-leader formation of unmanned vehicles following a desired trajectory. Incorporating the desired formation behavior provided by a ground operator, the locally implemented distributed controllers satisfy a previously established global performance index, leveraging only local information exchange in the decentralized formation.

Consider a fleet of unmanned vehicles moving through an environment under the direction of a single lead agent communicating with a ground operator. The topology of the communication structure is unknown to the operator, knowing only that it communicates with a single vehicle in the formation and provides a desired behavior for the formation as it moves along a series of predetermined waypoints. The formation establishes its leader based on the desired response from the ground operator and the knowledge of the formation structure, as determined exclusively through nearest-neighbor communication.

The contributions of this work are twofold. First, a novel approach to the decentralized selection of a formation leader establishes a leader best suited to follow a desired trajectory while adhering to the behavioral constraints requested by the ground operator. Second, an optimal control approach to a distributed controller design incorporates trajectory tracking and formation keeping through the underlying communication topology of the unmanned formation. This distributed design provides the leader with feedback from its followers, thereby reducing control usage by the followers to retain the formation structure and allows the leader to track the desired trajectory from the ground operator.},
	language = {en},
	urldate = {2024-06-25},
	author = {Robertson, Clay},
	month = aug,
	year = {2016},
	note = {Accepted: 2016-08-05T18:00:31Z},
}

In dynamic environments, the control of a formation of unmanned vehicles remains a significant control problem on both network and guidance dynamics levels. Currently, formations of unmanned vehicles require multiple ground operators to supervise the movement of a formation to effectively execute a task or mission objective. By designating a single vehicle as the lead agent of the formation, control over the entire formation reduces to a distribution of information through a single vehicle, thereby reducing the number of required ground operators. In such architectures, the location of the leader and the manner in which the control is distributed amongst the decentralized formation must suit the desired behavior requested by the ground operator. This work centers on the implementation of a single-leader formation of unmanned vehicles following a desired trajectory. Incorporating the desired formation behavior provided by a ground operator, the locally implemented distributed controllers satisfy a previously established global performance index, leveraging only local information exchange in the decentralized formation. Consider a fleet of unmanned vehicles moving through an environment under the direction of a single lead agent communicating with a ground operator. The topology of the communication structure is unknown to the operator, knowing only that it communicates with a single vehicle in the formation and provides a desired behavior for the formation as it moves along a series of predetermined waypoints. The formation establishes its leader based on the desired response from the ground operator and the knowledge of the formation structure, as determined exclusively through nearest-neighbor communication. The contributions of this work are twofold. First, a novel approach to the decentralized selection of a formation leader establishes a leader best suited to follow a desired trajectory while adhering to the behavioral constraints requested by the ground operator. Second, an optimal control approach to a distributed controller design incorporates trajectory tracking and formation keeping through the underlying communication topology of the unmanned formation. This distributed design provides the leader with feedback from its followers, thereby reducing control usage by the followers to retain the formation structure and allows the leader to track the desired trajectory from the ground operator.

@unpublished{pierce_incorporation_2016,
	title = {Incorporation of a {Foot}-{Mounted} {IMU} for {Multi}-{Sensor} {Pedestrian} {Navigation}},
	url = {https://etd.auburn.edu//handle/10415/5074},
	abstract = {This thesis deals with pedestrian localization by way of multi-sensor fusion. A special focus is made on the use of a foot-mounted inertial measurement unit (IMU) and its incorporation into other pedestrian navigation systems. Mounting to the foot location is preferred due to the anticipated dynamics of the foot during normal walking motion, but poses difficulty when fusing with other body-worn sensors. One of the main challenges lies in the non-rigid relation between navigation sources. This thesis approaches the problem by characterizing the human gait during walking motion and detecting instances in which spatial relations can be made. Navigational information of a pedestrian is often provided as a relative state measurement, such as step length, walking pace, rate of turn, etc. The fusion of multiple relative state measurements is non-trivial and requires manipulation of standard sensor fusion frameworks. Therefore, this thesis discusses certain frameworks for processing multiple relative state measurements in detail.
Two algorithms are presented for fusing a foot-mounted IMU with other body-worn relative state measurement systems. The first algorithm operates in a cascade architecture, which allows for easy implementation while still showing promising results. Drawbacks to the cascade architecture are discussed, and a second, centralized architecture is presented that addresses these issues. To serve as an example, a particular problem is addressed: fusing measurements from the foot-mounted IMU with a chest-mounted visual odometry system. By analyzing the human gait through the raw IMU signals, a relation is made between the position and orientation of the chest-mounted camera and the foot-mounted IMU. Using a high precision motion capture system, the human gait is analyzed and motion profiles of a typical step are calculated. Using these motion profiles as a basis, a simulation environment is developed to replicate visual odometry and foot-mounted IMU measurements and the navigation algorithms are applied to simulated data. Conclusions are drawn from simulation on the effectiveness of the respective algorithms and experimental data validates these findings. Experimental data is collected with an open source stereo visual odometry system and a MEMS grade IMU. In post-process, the experimental data is fed through the developed algorithms, and the results are compared to those found in simulation. The work presented in this thesis will inform the reader of the characteristics of a foot-mounted IMU solution and establish a methodology for fusing with any general pedestrian navigation device.},
	language = {en},
	urldate = {2024-06-25},
	author = {Pierce, Daniel},
	month = apr,
	year = {2016},
	note = {Accepted: 2016-04-29T19:38:32Z},
}

This thesis deals with pedestrian localization by way of multi-sensor fusion. A special focus is made on the use of a foot-mounted inertial measurement unit (IMU) and its incorporation into other pedestrian navigation systems. Mounting to the foot location is preferred due to the anticipated dynamics of the foot during normal walking motion, but poses difficulty when fusing with other body-worn sensors. One of the main challenges lies in the non-rigid relation between navigation sources. This thesis approaches the problem by characterizing the human gait during walking motion and detecting instances in which spatial relations can be made. Navigational information of a pedestrian is often provided as a relative state measurement, such as step length, walking pace, rate of turn, etc. The fusion of multiple relative state measurements is non-trivial and requires manipulation of standard sensor fusion frameworks. Therefore, this thesis discusses certain frameworks for processing multiple relative state measurements in detail. Two algorithms are presented for fusing a foot-mounted IMU with other body-worn relative state measurement systems. The first algorithm operates in a cascade architecture, which allows for easy implementation while still showing promising results. Drawbacks to the cascade architecture are discussed, and a second, centralized architecture is presented that addresses these issues. To serve as an example, a particular problem is addressed: fusing measurements from the foot-mounted IMU with a chest-mounted visual odometry system. By analyzing the human gait through the raw IMU signals, a relation is made between the position and orientation of the chest-mounted camera and the foot-mounted IMU. Using a high precision motion capture system, the human gait is analyzed and motion profiles of a typical step are calculated. Using these motion profiles as a basis, a simulation environment is developed to replicate visual odometry and foot-mounted IMU measurements and the navigation algorithms are applied to simulated data. Conclusions are drawn from simulation on the effectiveness of the respective algorithms and experimental data validates these findings. Experimental data is collected with an open source stereo visual odometry system and a MEMS grade IMU. In post-process, the experimental data is fed through the developed algorithms, and the results are compared to those found in simulation. The work presented in this thesis will inform the reader of the characteristics of a foot-mounted IMU solution and establish a methodology for fusing with any general pedestrian navigation device.

@unpublished{powell_multiple-antenna_2016,
	title = {A {Multiple}-{Antenna} {Software} {GPS} {Signal} {Simulator} for {Rapid} {Testing} of {Interference} {Mitigation} {Techniques}},
	url = {https://etd.auburn.edu//handle/10415/5520},
	abstract = {This thesis details the design of a software GPS signal simulator and illustrates how it can be used to support rapid testing of GPS interference mitigation research. The MATLAB-based signal simulator is capable of generating digital GPS signals at intermediate frequencies (IF) for multiple-element, controlled-radiation-pattern-antenna (CRPA) configurations in jamming environments. The simulator was developed to support novel GPS interference mitigation research conducted in the GPS and Vehicle Dynamics Laboratory at Auburn University. The digital signals can be analyzed with software acquisition, tracking, and positioning techniques or can be converted to analog signals at the GPS radio frequencies and played to multiple receivers via cabling using the Universal Software Radio Peripheral (USRP) software-defined-radio (SDR) platform. 


	 An IF GPS signal for a single antenna generated by the software simulator was played-back and recorded simultaneously with USRPs and compared to an IF signal for the same scenario generated by a hardware GPS simulator that was also recorded with a USRP. Position, velocity, pseudorange, Doppler frequency, and carrier-to-noise ratio measurements calculated by a software receiver from the simulated IF signal, the played-back and recorded IF signal, and the signal generated by the hardware simulator are compared to evaluate the baseline performance of the software simulator. Results of this experiment illustrate that a software simulator paired with the USRP is comparable in performance to the hardware simulator.  Additionally, a dynamic scenario generated by the software simulator was played-back and recorded with USRPs and also played to a hardware GPS receiver. Position results calculated by a software receiver from the simulated and played-back and recorded signals were compared to results calculated by the hardware receiver to further evaluate the performance of the software simulator. These results illustrate that the software simulator is capable of generating GPS signals for dynamic trajectories. 
	 

	To illustrate the capabilities provided by a software-based GPS simulator, signals along with three types of simulated jammers were generated and are illustrated in the frequency, time, and histogram domains . Each interference signal was played-back and recorded with USRPs, and results are provided to illustrate the steps that must be taken to capture the effects of simulated jammers in a USRP playback or record. Additionally, a 4-element CRPA interference simulation was generated by the software simulator and analyzed with a software receiver that was modified to include several interference mitigation techniques. Results provided by the modified software receiver illustrate that a software GPS simulator is a powerful tool for developing GPS interference mitigation techniques. Lastly, the simulated CRPA signals were played-back and recorded simultaneously with multiple USRPs to examine the feasibility of using relatively inexpensive SDRs to simulate multiple-antenna GPS scenarios. Results from this test illustrate that a multiple-USRP setup is a useful tool for testing robust interference mitigation techniques.},
	language = {en},
	urldate = {2024-06-25},
	author = {Powell, Russell},
	month = dec,
	year = {2016},
	note = {Accepted: 2016-12-12T15:34:31Z},
}

This thesis details the design of a software GPS signal simulator and illustrates how it can be used to support rapid testing of GPS interference mitigation research. The MATLAB-based signal simulator is capable of generating digital GPS signals at intermediate frequencies (IF) for multiple-element, controlled-radiation-pattern-antenna (CRPA) configurations in jamming environments. The simulator was developed to support novel GPS interference mitigation research conducted in the GPS and Vehicle Dynamics Laboratory at Auburn University. The digital signals can be analyzed with software acquisition, tracking, and positioning techniques or can be converted to analog signals at the GPS radio frequencies and played to multiple receivers via cabling using the Universal Software Radio Peripheral (USRP) software-defined-radio (SDR) platform. An IF GPS signal for a single antenna generated by the software simulator was played-back and recorded simultaneously with USRPs and compared to an IF signal for the same scenario generated by a hardware GPS simulator that was also recorded with a USRP. Position, velocity, pseudorange, Doppler frequency, and carrier-to-noise ratio measurements calculated by a software receiver from the simulated IF signal, the played-back and recorded IF signal, and the signal generated by the hardware simulator are compared to evaluate the baseline performance of the software simulator. Results of this experiment illustrate that a software simulator paired with the USRP is comparable in performance to the hardware simulator. Additionally, a dynamic scenario generated by the software simulator was played-back and recorded with USRPs and also played to a hardware GPS receiver. Position results calculated by a software receiver from the simulated and played-back and recorded signals were compared to results calculated by the hardware receiver to further evaluate the performance of the software simulator. These results illustrate that the software simulator is capable of generating GPS signals for dynamic trajectories. To illustrate the capabilities provided by a software-based GPS simulator, signals along with three types of simulated jammers were generated and are illustrated in the frequency, time, and histogram domains . Each interference signal was played-back and recorded with USRPs, and results are provided to illustrate the steps that must be taken to capture the effects of simulated jammers in a USRP playback or record. Additionally, a 4-element CRPA interference simulation was generated by the software simulator and analyzed with a software receiver that was modified to include several interference mitigation techniques. Results provided by the modified software receiver illustrate that a software GPS simulator is a powerful tool for developing GPS interference mitigation techniques. Lastly, the simulated CRPA signals were played-back and recorded simultaneously with multiple USRPs to examine the feasibility of using relatively inexpensive SDRs to simulate multiple-antenna GPS scenarios. Results from this test illustrate that a multiple-USRP setup is a useful tool for testing robust interference mitigation techniques.

@unpublished{morales_magnetometer_2016,
	title = {Magnetometer {Aided} {Navigation} {Filters} for {Improved} {Observability} and {Estimation} on {Ground} {Vehicles}},
	url = {https://etd.auburn.edu//handle/10415/5317},
	abstract = {Two modified extended Kalman filters, called the MGVA and MVVA filters, have been developed which combine the attitude determination capabilities of magnetometers with the standard extended Kalman filter. The standard extended Kalman filter is known to experience observability problems during driving which does not provide enough excitation to its sensors. The MGVA and MVVA filters attempt to remedy these problems by providing an attitude solution to the filter, via a process that utilizes magnetometer measurements. In order to show the effectiveness of the MGVA and MVVA filters, the filters were tested both in simulation, and experimentally for low excitation trajectories. It is shown in simulation that the two filters are able to improve attitude and accelerometer bias estimation in situations where the standard filter experiences estimation error. In addition to this, it is shown that both modified filters increase the observability rank of the system such that it is full rank. Experimental testing of the two modified filters reveals that both the MGVA and MVVA filters provide improved attitude and accelerometer bias estimation during low-excitation trajectories.

The MGVA and MVVA filters are also compared to a heading constrained filter that has been studied in the past. It is shown that the heading constrained filter produces more accurate estimates of heading than both of the modified filters. As a result, a further modification is implemented on both the MGVA and MVVA filters, and improved performance is shown for the MGVA filter. Finally, the MGVA and MVVA filters were tested on both simulated and experimental dynamic trajectories. This was done in order to test whether or not the filters are useful under typical trajectories that a ground vehicle might drive, not just low excitation trajectories. It is shown that under these circumstances the MGVA filter is suffers from the increased vehicle dynamics. In contrast, it is also shown that the MVVA filter is, once again, able to estimate attitude and accelerometer bias well. It is concluded from these tests that the MVVA filter is, in general preferable to the MGVA filter for more dynamic trajectories.},
	language = {en},
	urldate = {2024-06-25},
	author = {Morales, Gabriel},
	month = jul,
	year = {2016},
	note = {Accepted: 2016-07-29T20:52:45Z},
}

Two modified extended Kalman filters, called the MGVA and MVVA filters, have been developed which combine the attitude determination capabilities of magnetometers with the standard extended Kalman filter. The standard extended Kalman filter is known to experience observability problems during driving which does not provide enough excitation to its sensors. The MGVA and MVVA filters attempt to remedy these problems by providing an attitude solution to the filter, via a process that utilizes magnetometer measurements. In order to show the effectiveness of the MGVA and MVVA filters, the filters were tested both in simulation, and experimentally for low excitation trajectories. It is shown in simulation that the two filters are able to improve attitude and accelerometer bias estimation in situations where the standard filter experiences estimation error. In addition to this, it is shown that both modified filters increase the observability rank of the system such that it is full rank. Experimental testing of the two modified filters reveals that both the MGVA and MVVA filters provide improved attitude and accelerometer bias estimation during low-excitation trajectories. The MGVA and MVVA filters are also compared to a heading constrained filter that has been studied in the past. It is shown that the heading constrained filter produces more accurate estimates of heading than both of the modified filters. As a result, a further modification is implemented on both the MGVA and MVVA filters, and improved performance is shown for the MGVA filter. Finally, the MGVA and MVVA filters were tested on both simulated and experimental dynamic trajectories. This was done in order to test whether or not the filters are useful under typical trajectories that a ground vehicle might drive, not just low excitation trajectories. It is shown that under these circumstances the MGVA filter is suffers from the increased vehicle dynamics. In contrast, it is also shown that the MVVA filter is, once again, able to estimate attitude and accelerometer bias well. It is concluded from these tests that the MVVA filter is, in general preferable to the MGVA filter for more dynamic trajectories.

@unpublished{eick_nonlinear_2016,
	title = {A {Nonlinear} {Model} {Predictive} {Control} {Algorithm} for an {Unmanned} {Ground} {Vehicle} on {Variable} {Terrain}},
	url = {https://etd.auburn.edu//handle/10415/5517},
	abstract = {This thesis presents a Nonlinear Model Predictive Controller (NMPC) for an Unmanned Ground Vehicle (UGV) capable of controlling the vehicle over both smooth and rough terrain using measurements from GPS and a Light Detection And Ranging (LiDAR) unit equipped to the vehicle. Linear Model Predictive Control (MPC) and NMPC have become more widely used to control dynamic systems as computers have become more capable of handling the computational expense required by model predictive control. Though the use of NMPC rather than linear MPC creates an additional computational expense, NMPC allows for path planning in addition to control of the vehicle. This is particularly advantageous in scenarios in which the UGV is traversing terrain that contains obstacles of which the vehicle has no a priori knowledge. 

Rough, off-road terrain contains multiple hazards for an UGV. In this thesis, hazards are classified into three groups: obstacles, rough traversable terrain, and rough untraversable terrain. These three types of hazards create a rollover risk for a UGV. The NMPC presented in this thesis is designed to mitigate this risk of rollover. Simulations of the NMPC in several different scenarios are presented, as well as results from experimental implementation of the NMPC on a test vehicle. Results from simulation and experimental implementation are provided that show the NMPC is able to navigate a UGV around obstacles to a target location without requiring the use of a priori knowledge of terrain and obstacles.},
	language = {en},
	urldate = {2024-06-25},
	author = {Eick, Andrew},
	month = dec,
	year = {2016},
	note = {Accepted: 2016-12-12T15:21:00Z},
}

This thesis presents a Nonlinear Model Predictive Controller (NMPC) for an Unmanned Ground Vehicle (UGV) capable of controlling the vehicle over both smooth and rough terrain using measurements from GPS and a Light Detection And Ranging (LiDAR) unit equipped to the vehicle. Linear Model Predictive Control (MPC) and NMPC have become more widely used to control dynamic systems as computers have become more capable of handling the computational expense required by model predictive control. Though the use of NMPC rather than linear MPC creates an additional computational expense, NMPC allows for path planning in addition to control of the vehicle. This is particularly advantageous in scenarios in which the UGV is traversing terrain that contains obstacles of which the vehicle has no a priori knowledge. Rough, off-road terrain contains multiple hazards for an UGV. In this thesis, hazards are classified into three groups: obstacles, rough traversable terrain, and rough untraversable terrain. These three types of hazards create a rollover risk for a UGV. The NMPC presented in this thesis is designed to mitigate this risk of rollover. Simulations of the NMPC in several different scenarios are presented, as well as results from experimental implementation of the NMPC on a test vehicle. Results from simulation and experimental implementation are provided that show the NMPC is able to navigate a UGV around obstacles to a target location without requiring the use of a priori knowledge of terrain and obstacles.

@unpublished{britt_simultaneous_2016,
	title = {Simultaneous {Localization} {Auto}-{Calibration} and {Mapping} of {Ground} {Vehicles}},
	url = {https://etd.auburn.edu//handle/10415/5232},
	abstract = {This dissertation advances the state of the art of sensor auto-calibration by presenting a generic solution and analysis to the 3D sensor auto-calibration problem, as well as to the 2D simultaneous localization and auto-calibration (SLACAM) problem . Proper sensor calibration can be key to mission success when attempting to navigate robots in challenging environments. It allows for maximum information correlation between two sensors leading to higher fidelity representations of the environment thereby facilitating more precise navigation and obstacle avoidance, without which sub-optimal solutions such as taking longer paths to avoid obstacles to account for sensor error and other similar work arounds are employed. Additionally the ability to calibrate on the fly can greatly increase the robustness of a robot operating in challenging environments where canceling a mission prematurely is simply infeasible or not an option.
The ability to auto-calibrate two rigidly mounted sensors while on a moving platform will be validated using a rigidly mounted lidar and an inertial navigation system (INS) on a sport utility vehicle (SUV) while driving through an urban center. The presented technique will be compared to an independent party’s static laboratory calibration, which will show agreement to within tenths of degrees in angular accuracy and centimeter level translational accuracies. Additionally, the observability of this technique will be assessed and unobservable maneuvers will be highlighted. Additionally the three (DOF) alignment of an inertial measurement unit (IMU), lidar, and odometer system on a ground robot that is performing simultaneous localization and mapping (SLAM) will be assessed. Additionally the performance of the SLAM algorithm will be assessed as well as the observability of this system. This technique will demonstrate the ability to produce a navigation solution that accurately navigates the ground robot through a structured environment to within a robots length of the initial position while calibrating the lidar and odometer systems relative to the IMU to within the state of the art of single sensor calibration techniques.},
	language = {en},
	urldate = {2024-06-25},
	author = {Britt, Jordan},
	month = jun,
	year = {2016},
	note = {Accepted: 2016-06-17T19:57:42Z},
}

This dissertation advances the state of the art of sensor auto-calibration by presenting a generic solution and analysis to the 3D sensor auto-calibration problem, as well as to the 2D simultaneous localization and auto-calibration (SLACAM) problem . Proper sensor calibration can be key to mission success when attempting to navigate robots in challenging environments. It allows for maximum information correlation between two sensors leading to higher fidelity representations of the environment thereby facilitating more precise navigation and obstacle avoidance, without which sub-optimal solutions such as taking longer paths to avoid obstacles to account for sensor error and other similar work arounds are employed. Additionally the ability to calibrate on the fly can greatly increase the robustness of a robot operating in challenging environments where canceling a mission prematurely is simply infeasible or not an option. The ability to auto-calibrate two rigidly mounted sensors while on a moving platform will be validated using a rigidly mounted lidar and an inertial navigation system (INS) on a sport utility vehicle (SUV) while driving through an urban center. The presented technique will be compared to an independent party’s static laboratory calibration, which will show agreement to within tenths of degrees in angular accuracy and centimeter level translational accuracies. Additionally, the observability of this technique will be assessed and unobservable maneuvers will be highlighted. Additionally the three (DOF) alignment of an inertial measurement unit (IMU), lidar, and odometer system on a ground robot that is performing simultaneous localization and mapping (SLAM) will be assessed. Additionally the performance of the SLAM algorithm will be assessed as well as the observability of this system. This technique will demonstrate the ability to produce a navigation solution that accurately navigates the ground robot through a structured environment to within a robots length of the initial position while calibrating the lidar and odometer systems relative to the IMU to within the state of the art of single sensor calibration techniques.

@unpublished{ryan_classification_2016,
	title = {Classification of {Ego} {Platform} {Motion} for {Platform} {Independent} {Plug} and {Play} {Navigation}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/5142},
	abstract = {This dissertation presents a method of using these kinematic constraints without requiring this apriori knowledge of the application platform. The method is termed ``joint navigation and classification'' (JNC), and involves determining the platform type online and simultaneously using the platform type information to properly apply the kinematic constraints and improve accuracy. The JNC problem is solved with a form of multiple model particle filter which treats the platform type as a mode state upon which the navigation state vector is conditioned. The particle filter is marginalized using Rao-Blackwellization to improve computational efficiency. Additionally, this dissertation presents a method within the JNC particle filter of autonomously determining whether any constraints should be applied at all. Motivating this is a study which shows that applying constraints when the IMU is of high quality can actually hurt the solution. The final JNC particle filter is robust to this phenomenon. The algorithm is validated using data collected on three different platforms (ground vehicle, pedestrian, and aircraft) and with IMUs of varying quality. It is demonstrated that the JNC particle filter can autonomously determine the correct platform type and use that knowledge to improve the navigation solution. It is further demonstrated that the JNC filter can autonomously detect situations where it is advantageous not to apply the constraints, thereby avoiding the pitfall described above. The JNC particle filter offers a best of both worlds solution which is both flexible and optimized to the platform, in addition to being robust to situations with high quality IMUs. Many navigation systems take advantage of knowledge of the host platform type, such as a ground vehicle, to apply kinematic constraints to the system to improve the navigation solution. It has been well documented that such constraints can help reduce inertial drift, whether in concert with other aiding sensors or as the only aids to an otherwise unaided inertial system. However, using these constraints implies an apriori knowledge of the host platform type during the design phase. This is commonly done and is acceptable for stovepiped solutions for which flexibility is not a concern. However, this does not allow for flexibility in either the design phase or in the field.},
	language = {en},
	urldate = {2024-06-25},
	author = {Ryan, Jonathan},
	month = may,
	year = {2016},
	note = {Accepted: 2016-05-05T16:03:09Z},
}

This dissertation presents a method of using these kinematic constraints without requiring this apriori knowledge of the application platform. The method is termed ``joint navigation and classification'' (JNC), and involves determining the platform type online and simultaneously using the platform type information to properly apply the kinematic constraints and improve accuracy. The JNC problem is solved with a form of multiple model particle filter which treats the platform type as a mode state upon which the navigation state vector is conditioned. The particle filter is marginalized using Rao-Blackwellization to improve computational efficiency. Additionally, this dissertation presents a method within the JNC particle filter of autonomously determining whether any constraints should be applied at all. Motivating this is a study which shows that applying constraints when the IMU is of high quality can actually hurt the solution. The final JNC particle filter is robust to this phenomenon. The algorithm is validated using data collected on three different platforms (ground vehicle, pedestrian, and aircraft) and with IMUs of varying quality. It is demonstrated that the JNC particle filter can autonomously determine the correct platform type and use that knowledge to improve the navigation solution. It is further demonstrated that the JNC filter can autonomously detect situations where it is advantageous not to apply the constraints, thereby avoiding the pitfall described above. The JNC particle filter offers a best of both worlds solution which is both flexible and optimized to the platform, in addition to being robust to situations with high quality IMUs. Many navigation systems take advantage of knowledge of the host platform type, such as a ground vehicle, to apply kinematic constraints to the system to improve the navigation solution. It has been well documented that such constraints can help reduce inertial drift, whether in concert with other aiding sensors or as the only aids to an otherwise unaided inertial system. However, using these constraints implies an apriori knowledge of the host platform type during the design phase. This is commonly done and is acceptable for stovepiped solutions for which flexibility is not a concern. However, this does not allow for flexibility in either the design phase or in the field.

@unpublished{li_modelling_2016,
	title = {Modelling, {Control} and {Estimation} {Techniques} {For} {Micromachined} {Electrostatic} {Actuators} {Using} {Macro} {Magnetic} {Actuators}},
	url = {https://etd.auburn.edu//handle/10415/5321},
	abstract = {Parallel plate actuators (PPAs) are fundamental devices in micro-electro-mechanical systems. PPAs' main drawback is their limited open loop stable traveling range which is caused by their nonlinear electrostatic force. Thus, feedback control techniques are required in applications which need large  and precision motions. However, controlling and analyzing PPAs' behavior could be limited by several factors. The fabrication process of PPAs is expensive; the miniatured dimension of PPAs makes motion detection and experimental setup difficult.

This dissertation proposes an alternative approach to prototype analysis, control and estimation techniques for PPAs by investigating PPAs' dual systems, which are macro magnetic type solenoids. Solenoids have the similar kinematics and their stable traveling range is affected by the nonlinear magnetic force. As a test component, the advantages of solenoids include the low cost and macro size which is convenient to package and detection.

An iterative solution method is developed to study the behaviors of the actuators in circuity environment. 
First, the expressions of the time-variant capacitor in a PPA, AC source and their derivatives with respect to time are determined. An approximated solution combining the initial solution and its iteratively derived higher-order terms is reached. Then, the time-variant inductor in a solenoid with a restrained condition that the circuit is powered by DC sources is modeled. The iterative solution using a small signal theorem is also employed to obtain an approximate closed form solution for the time variant inductor.
The simulation and experimental study further demonstrated that: (i) this iterative solution can effectively analyze the dynamics of the square law devices with a time-variant capacitor or inductor; and (ii) computing additional higher-order terms derived from the initial solution can further improve the solution’s accuracy.

A practical disturbance controller is developed to extend stable range of solenoids, which could be also extended to PPAs.
The input–output linearization control method is an effective technique to extend the stable range. But in practice, however, the time-delay effect from both measurement and actuation can make the system less damped and therefore more sensitive to disturbances. This effect was analyzed and a digital proportional and integrator controller plus extended state observer (ESO) is proposed to enhance the performance of the electromagnetic actuator. Simulation and experimental tests show that this combined proportional and integral and ESO technique can extend the stable range of motion to 77.6 {\textbackslash}\% of full stroke with less sensitivity to external disturbances.

The feasibility of transplanting self sensing from solenoids to PPAs is investigated. The observability improvement of PPA design is investigated. This study proposes an alternative approach of designing an estimator using the measured voltage across the PPA without additional sensing structures and distortions. This novel method can improve the performance and reduce the device's footprint with full state (displacement and velocity) feedback information, using a series resistor. A system model using this configuration is investigated. The observability of this self-sensing technique is analyzed using a small signal model. Then, a singular value decomposition (SVD) is applied to examine how to further improve the observability by choosing appropriate parameters. Simulation and numerical studies were performed which validate this method.},
	language = {en},
	urldate = {2024-06-25},
	author = {Li, Chong},
	month = jul,
	year = {2016},
	note = {Accepted: 2016-07-29T21:13:48Z},
}

Parallel plate actuators (PPAs) are fundamental devices in micro-electro-mechanical systems. PPAs' main drawback is their limited open loop stable traveling range which is caused by their nonlinear electrostatic force. Thus, feedback control techniques are required in applications which need large and precision motions. However, controlling and analyzing PPAs' behavior could be limited by several factors. The fabrication process of PPAs is expensive; the miniatured dimension of PPAs makes motion detection and experimental setup difficult. This dissertation proposes an alternative approach to prototype analysis, control and estimation techniques for PPAs by investigating PPAs' dual systems, which are macro magnetic type solenoids. Solenoids have the similar kinematics and their stable traveling range is affected by the nonlinear magnetic force. As a test component, the advantages of solenoids include the low cost and macro size which is convenient to package and detection. An iterative solution method is developed to study the behaviors of the actuators in circuity environment. First, the expressions of the time-variant capacitor in a PPA, AC source and their derivatives with respect to time are determined. An approximated solution combining the initial solution and its iteratively derived higher-order terms is reached. Then, the time-variant inductor in a solenoid with a restrained condition that the circuit is powered by DC sources is modeled. The iterative solution using a small signal theorem is also employed to obtain an approximate closed form solution for the time variant inductor. The simulation and experimental study further demonstrated that: (i) this iterative solution can effectively analyze the dynamics of the square law devices with a time-variant capacitor or inductor; and (ii) computing additional higher-order terms derived from the initial solution can further improve the solution’s accuracy. A practical disturbance controller is developed to extend stable range of solenoids, which could be also extended to PPAs. The input–output linearization control method is an effective technique to extend the stable range. But in practice, however, the time-delay effect from both measurement and actuation can make the system less damped and therefore more sensitive to disturbances. This effect was analyzed and a digital proportional and integrator controller plus extended state observer (ESO) is proposed to enhance the performance of the electromagnetic actuator. Simulation and experimental tests show that this combined proportional and integral and ESO technique can extend the stable range of motion to 77.6 \% of full stroke with less sensitivity to external disturbances. The feasibility of transplanting self sensing from solenoids to PPAs is investigated. The observability improvement of PPA design is investigated. This study proposes an alternative approach of designing an estimator using the measured voltage across the PPA without additional sensing structures and distortions. This novel method can improve the performance and reduce the device's footprint with full state (displacement and velocity) feedback information, using a series resistor. A system model using this configuration is investigated. The observability of this self-sensing technique is analyzed using a small signal model. Then, a singular value decomposition (SVD) is applied to examine how to further improve the observability by choosing appropriate parameters. Simulation and numerical studies were performed which validate this method.

@inproceedings{carson_gps_2016,
	title = {{GPS} spoofing detection and mitigation using {Cooperative} {Adaptive} {Cruise} {Control} system: 2016 {IEEE} {Intelligent} {Vehicles} {Symposium} ({IV}), {Intelligent} {Vehicles} {Symposium} ({IV}), 2016 {IEEE}},
	shorttitle = {{GPS} spoofing detection and mitigation using {Cooperative} {Adaptive} {Cruise} {Control} system},
	doi = {10.1109/IVS.2016.7535525},
	abstract = {Global Navigation Satellite Systems (GNSS) like the Global Positioning System (GPS) are susceptible to electronic interference which threatens the reliability of the systems outputs, precise time and localization. Interference comes from natural and predatory sources in the form of increased in-band noise and structured attacks. The structured attack, called spoofing, is designed to trick the receiver into reporting an incorrect navigation solution as if it were accurate. Modern automobiles are becoming more reliant on GPS for localization, automation, and safety. Vehicles are also equipped with a variety of sensors (e.g. Radars, Lidars, wheel encoders) that provide situational awareness which may be leveraged in a GPS spoofing detection scheme. The proposed spoofing detection and mitigation system relies on an existing Cooperative Adaptive Cruise Control (CACC) system to provide inter-vehicle ranging and data sharing. The inter-vehicle ranges are used to detect a spoofing attack, and the mitigation system removes the attacking signal from the incoming data stream. The spoofing detection and removal system is tested using data recorded with a fielded CACC system on two commercial trucks. Intermediate frequency (IF) GPS data is collected during the test. Since live sky spoofing is legal, the IF data recording allows for post process spoofing injection in a controlled environment. In post process, the spoofing signal is shown to “capture” the onboard GPS receiver. The proposed system uses the spoofed IF GPS data along with recorded observables from the CACC system to detection and remove the attack.},
	booktitle = {2016 {IEEE} {Intelligent} {Vehicles} {Symposium} ({IV}), {Intelligent} {Vehicles} {Symposium} ({IV}), 2016 {IEEE}},
	author = {Carson, Nathaniel and Martin, Scott M. and Starling, Joshua and Bevly, David M.},
	month = jun,
	year = {2016},
	keywords = {Adaptive systems, Communication, Networking and Broadcast Technologies, Cruise control, Delay effects, Global Positioning System, Receivers, Robotics and Control Systems, Satellites, Signal Processing and Analysis, Transportation, Vehicles},
	pages = {1091--1096},
}

Global Navigation Satellite Systems (GNSS) like the Global Positioning System (GPS) are susceptible to electronic interference which threatens the reliability of the systems outputs, precise time and localization. Interference comes from natural and predatory sources in the form of increased in-band noise and structured attacks. The structured attack, called spoofing, is designed to trick the receiver into reporting an incorrect navigation solution as if it were accurate. Modern automobiles are becoming more reliant on GPS for localization, automation, and safety. Vehicles are also equipped with a variety of sensors (e.g. Radars, Lidars, wheel encoders) that provide situational awareness which may be leveraged in a GPS spoofing detection scheme. The proposed spoofing detection and mitigation system relies on an existing Cooperative Adaptive Cruise Control (CACC) system to provide inter-vehicle ranging and data sharing. The inter-vehicle ranges are used to detect a spoofing attack, and the mitigation system removes the attacking signal from the incoming data stream. The spoofing detection and removal system is tested using data recorded with a fielded CACC system on two commercial trucks. Intermediate frequency (IF) GPS data is collected during the test. Since live sky spoofing is legal, the IF data recording allows for post process spoofing injection in a controlled environment. In post process, the spoofing signal is shown to “capture” the onboard GPS receiver. The proposed system uses the spoofed IF GPS data along with recorded observables from the CACC system to detection and remove the attack.

@inproceedings{bevly_lane_2016,
	title = {Lane {Change} and {Merge} {Maneuvers} for {Connected} and {Automated} {Vehicles}: {A} {Survey}},
	volume = {1},
	shorttitle = {Lane {Change} and {Merge} {Maneuvers} for {Connected} and {Automated} {Vehicles}},
	url = {https://ieeexplore.ieee.org/abstract/document/7515222},
	doi = {10.1109/TIV.2015.2503342},
	abstract = {Intelligence in vehicles has developed through the years as self-driving expectations and capabilities have increased. To date, the majority of the literature has focused on longitudinal control topics (e.g. Adaptive Cruise Control (ACC), Cooperative ACC (CACC), etc.). To a lesser extent, there have been a variety of research articles specifically dealing with lateral control, e.g., maneuvers such as lane changes and merging. This paper provides a survey of this particular area of vehicle automation. The key topics addressed are control systems, positioning systems, communication systems, simulation modeling, field tests, surroundings vehicles, and human factors. Overall, there has been some successful research and field testing in lane change and merge maneuvers; however, there is a strong need for standardization and even more research to enable comprehensive field testing of these lateral maneuvers, so that commercial implementation of automated vehicles can be realized.},
	urldate = {2024-06-20},
	booktitle = {{IEEE} {Transactions} on {Intelligent} {Vehicles}},
	author = {Bevly, David and Cao, Xiaolong and Gordon, Mikhail and Ozbilgin, Guchan and Kari, David and Nelson, Brently and Woodruff, Jonathan and Barth, Matthew and Murray, Chase and Kurt, Arda and Redmill, Keith and Ozguner, Umit},
	month = mar,
	year = {2016},
	keywords = {Automation, Cooperative adaptive cruise control (CACC), Cruise control, Global Positioning System, Intelligent vehicles, Laser radar, Predictive control, dedicated short range communications (DSRC), differential global positioning system (DGPS), lane change and merge, light detection and ranging (LiDAR), managed lanes, model predictive control (MPC), platooning, real time kinematic (RTK)},
	pages = {105--120},
}

Intelligence in vehicles has developed through the years as self-driving expectations and capabilities have increased. To date, the majority of the literature has focused on longitudinal control topics (e.g. Adaptive Cruise Control (ACC), Cooperative ACC (CACC), etc.). To a lesser extent, there have been a variety of research articles specifically dealing with lateral control, e.g., maneuvers such as lane changes and merging. This paper provides a survey of this particular area of vehicle automation. The key topics addressed are control systems, positioning systems, communication systems, simulation modeling, field tests, surroundings vehicles, and human factors. Overall, there has been some successful research and field testing in lane change and merge maneuvers; however, there is a strong need for standardization and even more research to enable comprehensive field testing of these lateral maneuvers, so that commercial implementation of automated vehicles can be realized.

@inproceedings{humphreys_evaluation_2016,
	title = {An {Evaluation} of the {Fuel} {Economy} {Benefits} of a {Driver} {Assistive} {Truck} {Platooning} {Prototype} {Using} {Simulation}},
	url = {https://www.sae.org/content/2016-01-0167/},
	doi = {10.4271/2016-01-0167},
	urldate = {2024-06-20},
	author = {Humphreys, Hugh Luke and Batterson, Joshua and Bevly, David and Schubert, Raymond},
	month = apr,
	year = {2016},
	pages = {2016--01--0167},
}

@inproceedings{rose_blind_2016,
	title = {Blind {Pedestrian} {Body}-{Worn} {Navigational} {Aid} {Based} on {Pedometry} and {Smart} {Intersection} {Connectivity}},
	url = {https://trid.trb.org/View/1394111},
	urldate = {2024-06-20},
	author = {Rose, Christopher and Pierce, Daniel and Gao, Song and Cofield, Robert and Bevly, David M. and Bishop, Richard},
	year = {2016},
}

@unpublished{preston_gps_2015,
	title = {{GPS} {Multipath} {Detection} and {Mitigation} {Timing} {Bias} {Techniques}},
	url = {https://etd.auburn.edu//handle/10415/4611},
	abstract = {In this thesis, timing-based methods of multipath mitigation and detection are developed.
GPS pseudorange measurements are used to calculate a receiver's position and timing
bias, which is a measurement of the di erence between the GPS satellite clocks and receiver
clock. The timing bias will be monitored while the receiver is disciplined with a chip-scale
atomic clock (CSAC), which has exceptional stability and accuracy, and has recently been
made available to the public at an a ordable cost. The CSAC controls the receiver's timing
bias drift rate, allowing for the use of the timing bias to detect multipath and spoo ng. Under
normal operation, the clock in a GPS receiver drifts too rapidly to be used for multipath
detection, and must the timing bias must always be solved for as a nuisance parameter.
Di erent grades of clocks will be examined in a benign environment to attain accurate
models of the speci c clocks being used, and to determine what the clock drifts are without
external in
uences. The clock models will then be used to detect multipath in a dynamic test.
After detection, an algorithm to remove faulty GPS signals will be implemented, creating
an accurate, multipath-free position solution. In addition to detecting multipath, the clock
model will provide a reasonable estimate of the clock drift when there are fewer than four
satellites available. This allows for a reduction from four to three satellites needed to solve
for position, as well as the ability to predict clock drift during a GPS outage. Finally, a
spoo ng simulation will be outlined and simulated using a low-cost ublox receiver. The
ublox clock is not as good as a CSAC, but performs acceptably for determining whether or
not the receiver is being spoofed.},
	language = {en},
	urldate = {2024-06-25},
	author = {Preston, Sarah},
	month = may,
	year = {2015},
	note = {Accepted: 2015-05-08T13:55:11Z},
}

In this thesis, timing-based methods of multipath mitigation and detection are developed. GPS pseudorange measurements are used to calculate a receiver's position and timing bias, which is a measurement of the di erence between the GPS satellite clocks and receiver clock. The timing bias will be monitored while the receiver is disciplined with a chip-scale atomic clock (CSAC), which has exceptional stability and accuracy, and has recently been made available to the public at an a ordable cost. The CSAC controls the receiver's timing bias drift rate, allowing for the use of the timing bias to detect multipath and spoo ng. Under normal operation, the clock in a GPS receiver drifts too rapidly to be used for multipath detection, and must the timing bias must always be solved for as a nuisance parameter. Di erent grades of clocks will be examined in a benign environment to attain accurate models of the speci c clocks being used, and to determine what the clock drifts are without external in uences. The clock models will then be used to detect multipath in a dynamic test. After detection, an algorithm to remove faulty GPS signals will be implemented, creating an accurate, multipath-free position solution. In addition to detecting multipath, the clock model will provide a reasonable estimate of the clock drift when there are fewer than four satellites available. This allows for a reduction from four to three satellites needed to solve for position, as well as the ability to predict clock drift during a GPS outage. Finally, a spoo ng simulation will be outlined and simulated using a low-cost ublox receiver. The ublox clock is not as good as a CSAC, but performs acceptably for determining whether or not the receiver is being spoofed.

@unpublished{mcintyre_study_2015,
	title = {A {Study} of {Lateral} and {Longitudinal} {Tire} {Forces} {Produced} on a {Deformable} {Surface} with {Applied} {Traction} and {Braking}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/4630},
	abstract = {An investigation into the effects that changing tire characteristics have on the production of lateral and longitudinal tire forces was conducted on a test wheel that was subjected to external traction and braking forces. The test tire’s slip angle, camber, inflation pressure and normal load were adjusted as the test wheel was run over a prepared piece of deformable test terrain consisting of a fine particle, remolded clay. Force data was collected using a series of load cells and tire angular velocity was collected from a Hall Effect senor and encoder wheel. The data was analyzed and several conclusions were reached about the effects that the tire characteristics have on both lateral and longitudinal force production. Tire friction ellipses were also created using the collected data to provide a more complete picture of the tire’s performance during combined slip conditions i.e. a vehicle maneuvering with applied traction.},
	language = {en},
	urldate = {2024-06-25},
	author = {McIntyre, David Michael},
	month = may,
	year = {2015},
	note = {Accepted: 2015-05-11T13:21:43Z},
}

An investigation into the effects that changing tire characteristics have on the production of lateral and longitudinal tire forces was conducted on a test wheel that was subjected to external traction and braking forces. The test tire’s slip angle, camber, inflation pressure and normal load were adjusted as the test wheel was run over a prepared piece of deformable test terrain consisting of a fine particle, remolded clay. Force data was collected using a series of load cells and tire angular velocity was collected from a Hall Effect senor and encoder wheel. The data was analyzed and several conclusions were reached about the effects that the tire characteristics have on both lateral and longitudinal force production. Tire friction ellipses were also created using the collected data to provide a more complete picture of the tire’s performance during combined slip conditions i.e. a vehicle maneuvering with applied traction.

@unpublished{keyser_design_2015,
	title = {Design and {Implementation} of a {SoC}-{Based} {Real}-{Time} {Vector} {Tracking} {GPS} {Receiver}},
	url = {https://etd.auburn.edu//handle/10415/4580},
	abstract = {This thesis provides the design and implementation of a GPS receiver which utilizes advanced tracking algorithms on a small, low cost platform. The tracking algorithms used are of a class of algorithms known as vector tracking. Vector tracking receivers have been known to have an increased immunity to jamming and maintain signal lock on weaker signals. These benefits often come at the price of computation time, as the algorithms can require extensive matrix inversion and impose critical timing requirements on the receiver. To handle the computational burdens, a system-on-chip implementation was chosen using the Xilinx Zynq architecture. This architecture couples an FPGA with a dual-core ARM processor in a small package and can be acquired on development boards at a low cost. This thesis demonstrates how this architecture is utilized to overcome the strict timing requirements of a real-time vector tracking GPS receiver. The design and implementation of the receiver is described such that it can be used as an aide in the development of other advanced acquisition, tracking, or navigation algorithms. Performance results are given in regards to tracking, positions, and processing times.},
	language = {en},
	urldate = {2024-06-25},
	author = {Keyser, Brian},
	month = may,
	year = {2015},
	note = {Accepted: 2015-05-06T20:15:10Z},
}

This thesis provides the design and implementation of a GPS receiver which utilizes advanced tracking algorithms on a small, low cost platform. The tracking algorithms used are of a class of algorithms known as vector tracking. Vector tracking receivers have been known to have an increased immunity to jamming and maintain signal lock on weaker signals. These benefits often come at the price of computation time, as the algorithms can require extensive matrix inversion and impose critical timing requirements on the receiver. To handle the computational burdens, a system-on-chip implementation was chosen using the Xilinx Zynq architecture. This architecture couples an FPGA with a dual-core ARM processor in a small package and can be acquired on development boards at a low cost. This thesis demonstrates how this architecture is utilized to overcome the strict timing requirements of a real-time vector tracking GPS receiver. The design and implementation of the receiver is described such that it can be used as an aide in the development of other advanced acquisition, tracking, or navigation algorithms. Performance results are given in regards to tracking, positions, and processing times.

@unpublished{cao_design_2015,
	title = {Design and {Experimental} {Validation} of {Longitudinal} {Controller} of {Connected} {Vehicles} using {Model} {Predictive} {Control}},
	url = {https://etd.auburn.edu//handle/10415/4989},
	abstract = {In this thesis, a vehicle longitudinal control algorithm based on model predictive control (MPC) is applied to compute the desired relative acceleration of the following vehicle in leader-follower systems. Kinematic equations are used to describe the dynamic relationship between the leading and following vehicles. Compared to the conventional model predictive control (CMPC), the control horizon is expressed using Laguerre functions. This makes the optimization problem easier to solve and available to be tuned. Appropriate parameters are investigated by comparing the different approximation results under different decay factors. The design of MPC based on Laguerre functions (LMPC) enables the system to be adjustable through the selection of the decay factors depending on the characteristics such as response time and overshoot of the closed-loop system. The effectiveness of the design approach was demonstrated using simulations and experiments. Control performance of the closed-loop system was investigated by selecting different parameters including the states weighting matrix, the input weighting matrix, and Laguerre coefficients. With constraints on the control variables and the difference of the control variables, the following vehicle can track the leading vehicle with a specific distance and at the same speed in the simulation. Experiments which illustrate the performance of the control system were performed on an experimental platform used by Federal Highway Administration (FHWA), followed by the experimental data showing the following vehicle can track the leading vehicle with a specific distance and at the same speed. However, there is overshoot of the distance and the relative speed is not zero. The reasons of the poor performance of the control system were explored, which include the absence of the acceleration of the leading vehicle, large constraints on the difference of the desired acceleration. Solutions such as decreasing the constraints on the incremental variation and enlarging the input weighting matrix are discussed.},
	language = {en},
	urldate = {2024-06-25},
	author = {Cao, Xiaolong},
	month = dec,
	year = {2015},
	note = {Accepted: 2015-12-14T16:51:26Z},
}

In this thesis, a vehicle longitudinal control algorithm based on model predictive control (MPC) is applied to compute the desired relative acceleration of the following vehicle in leader-follower systems. Kinematic equations are used to describe the dynamic relationship between the leading and following vehicles. Compared to the conventional model predictive control (CMPC), the control horizon is expressed using Laguerre functions. This makes the optimization problem easier to solve and available to be tuned. Appropriate parameters are investigated by comparing the different approximation results under different decay factors. The design of MPC based on Laguerre functions (LMPC) enables the system to be adjustable through the selection of the decay factors depending on the characteristics such as response time and overshoot of the closed-loop system. The effectiveness of the design approach was demonstrated using simulations and experiments. Control performance of the closed-loop system was investigated by selecting different parameters including the states weighting matrix, the input weighting matrix, and Laguerre coefficients. With constraints on the control variables and the difference of the control variables, the following vehicle can track the leading vehicle with a specific distance and at the same speed in the simulation. Experiments which illustrate the performance of the control system were performed on an experimental platform used by Federal Highway Administration (FHWA), followed by the experimental data showing the following vehicle can track the leading vehicle with a specific distance and at the same speed. However, there is overshoot of the distance and the relative speed is not zero. The reasons of the poor performance of the control system were explored, which include the absence of the acceleration of the leading vehicle, large constraints on the difference of the desired acceleration. Solutions such as decreasing the constraints on the incremental variation and enlarging the input weighting matrix are discussed.

@unpublished{yu_optimization_2015,
	title = {Optimization {Approaches} for a {Dubins} {Vehicle} in {Coverage} {Planning} {Problem} and {Traveling} {Salesman} {Problems}},
	url = {https://etd.auburn.edu//handle/10415/4599},
	abstract = {The motivation of this dissertation is a path planning task for an autonomous robot-trailer system in geophysical surveys. The path planning task includes two main stages. In the first stage, an efficient coverage path is required to obtain a fully sensor coverage of a site to provide a complete map of anomalies. After the locations of anomalies are determined, in the second stage, an efficient traversal path is required to visit these anomalies to mark or obtain more data for further identification. The first stage can be regarded as the coverage path planning problem and the second stage can be regarded as a special case of traveling salesman problem. The robot-trailer system is modeled as a Dubins vehicle that can only move forward and turn with upper bounded curvature. Motivated by this autonomous inspection task, the author makes several contributions to the solution of coverage path planning problem and the solution of traveling salesman problems.

In the coverage path planning, the author presents an optimization approach that takes the vehicle's characteristics into account to minimize the non-working travel of the vehicle. Since turns are often costly for Dubins vehicle, minimizing the cost of turns usually produces more working efficiency. Prior researches on coverage path planning tend to fall into two complementary categories: (1) minimize the number of turns, by finding the optimal decomposition of a complex field into subfields and the optimal driving directions; (2) minimize the cost on a fixed number of turns, by finding the optimal visiting sequence of subfields and the optimal traversal sequence of parallel tracks for each subfield. This dissertation firstly presents a new algorithm to find the optimal decomposition that belongs to the first category; then designs a novel traversal pattern of parallel field tracks that belongs to the second category; finally extends the proposed traversal pattern to connect with the decomposition approach in the first category, providing a complete coverage path planning method for the mobile robot. Experiments show that the proposed method can provide feasible solutions and the total wasted distance can be greatly reduced, when compared against classical boustrophedon path or recent state-of-the-art.

In the traveling salesman problems, given a set of waypoints and the turning constraint on the vehicle, the addressed problem is to determine a visiting sequence of these waypoints, and to assign a configuration of the vehicle at each waypoint. The objective function is to minimize the total distances traveled by the vehicle. 
A genetic algorithm is designed to find the shortest path and the performance is evaluated in numerical study. The proposed genetic algorithm can perform very well in both low waypoint density and high waypoint density situations. The author then takes the sensor scope into consideration to further minimize the total travel distance. The problem can be regarded as a special case of the Traveling Salesman Problem with Neighborhoods (TSPN). The concept of a neighborhood is used to model the physical size of the sensor scope. The neighborhoods are represented by disks in this dissertation. The author uses a two-step approach to solve the problem: (1) design a new algorithm for the TSPN to search the optimal visiting sequence and entry positions; (2) design a new algorithm for the Dubins vehicle to determine the heading at each entry position. The theoretical and numerical studies show that the proposed approach can perform very well for both disjoint and overlapped disks cases. The practical experiment shows that the model is feasible for the robot-trailer application. 

While the authors focus on a robot-trailer system in this dissertation, the proposed algorithm could be applied to any Dubins vehicle that has similar mission requirements.},
	language = {en},
	urldate = {2024-06-25},
	author = {Yu, Xin},
	month = may,
	year = {2015},
	note = {Accepted: 2015-05-07T20:41:10Z},
}

The motivation of this dissertation is a path planning task for an autonomous robot-trailer system in geophysical surveys. The path planning task includes two main stages. In the first stage, an efficient coverage path is required to obtain a fully sensor coverage of a site to provide a complete map of anomalies. After the locations of anomalies are determined, in the second stage, an efficient traversal path is required to visit these anomalies to mark or obtain more data for further identification. The first stage can be regarded as the coverage path planning problem and the second stage can be regarded as a special case of traveling salesman problem. The robot-trailer system is modeled as a Dubins vehicle that can only move forward and turn with upper bounded curvature. Motivated by this autonomous inspection task, the author makes several contributions to the solution of coverage path planning problem and the solution of traveling salesman problems. In the coverage path planning, the author presents an optimization approach that takes the vehicle's characteristics into account to minimize the non-working travel of the vehicle. Since turns are often costly for Dubins vehicle, minimizing the cost of turns usually produces more working efficiency. Prior researches on coverage path planning tend to fall into two complementary categories: (1) minimize the number of turns, by finding the optimal decomposition of a complex field into subfields and the optimal driving directions; (2) minimize the cost on a fixed number of turns, by finding the optimal visiting sequence of subfields and the optimal traversal sequence of parallel tracks for each subfield. This dissertation firstly presents a new algorithm to find the optimal decomposition that belongs to the first category; then designs a novel traversal pattern of parallel field tracks that belongs to the second category; finally extends the proposed traversal pattern to connect with the decomposition approach in the first category, providing a complete coverage path planning method for the mobile robot. Experiments show that the proposed method can provide feasible solutions and the total wasted distance can be greatly reduced, when compared against classical boustrophedon path or recent state-of-the-art. In the traveling salesman problems, given a set of waypoints and the turning constraint on the vehicle, the addressed problem is to determine a visiting sequence of these waypoints, and to assign a configuration of the vehicle at each waypoint. The objective function is to minimize the total distances traveled by the vehicle. A genetic algorithm is designed to find the shortest path and the performance is evaluated in numerical study. The proposed genetic algorithm can perform very well in both low waypoint density and high waypoint density situations. The author then takes the sensor scope into consideration to further minimize the total travel distance. The problem can be regarded as a special case of the Traveling Salesman Problem with Neighborhoods (TSPN). The concept of a neighborhood is used to model the physical size of the sensor scope. The neighborhoods are represented by disks in this dissertation. The author uses a two-step approach to solve the problem: (1) design a new algorithm for the TSPN to search the optimal visiting sequence and entry positions; (2) design a new algorithm for the Dubins vehicle to determine the heading at each entry position. The theoretical and numerical studies show that the proposed approach can perform very well for both disjoint and overlapped disks cases. The practical experiment shows that the model is feasible for the robot-trailer application. While the authors focus on a robot-trailer system in this dissertation, the proposed algorithm could be applied to any Dubins vehicle that has similar mission requirements.

@inproceedings{wang_mobility_2015,
	title = {Mobility improves {LMI}-based cooperative indoor localization},
	url = {https://ieeexplore.ieee.org/document/7127811/;jsessionid=9D59D8946E719F5CF86D9860D7531EA2},
	doi = {10.1109/WCNC.2015.7127811},
	abstract = {With the proliferation of mobile devices such as smartphones, an interesting problem is how to make use them to improve the accuracy of localization in indoor environments. In this paper, we develop a novel cooperative localization scheme exploiting mobility in the indoor environment. The problem is formulated as a semidefinite program (SDP) using Linear Matrix Inequality (LMI). With the proposed approach, mobile users utilize their top RSS measurements for distance estimation and to mitigate the the shadowing effect found in indoor environments. In addition, we utilize the estimated position for a user from the last time slot as a virtual access point (AP) to obtain the next position estimation, by utilizing the inertial measurement unit (IMU) data from smartphones. To better take advantage of the moving direction and velocity information provided by the smartphones, we next apply Kalman filter to further mitigate the errors in estimated positions. Simulation results confirm that both the mean error and variance can be effectively reduced by exploiting IMU data and Kalman filter.},
	urldate = {2024-06-20},
	booktitle = {2015 {IEEE} {Wireless} {Communications} and {Networking} {Conference} ({WCNC})},
	author = {Wang, Xuyu and Zhou, Hui and Mao, Shiwen and Pandey, Santosh and Agrawal, Prathima and Bevly, David M.},
	month = mar,
	year = {2015},
	note = {ISSN: 1558-2612},
	keywords = {Accuracy, Estimation, Gaussian-Newton algorithm, Indoor environments, Kalman filter, Kalman filters, Mobile communication, Smart phones, Standards, indoor localization, linear matrix inequality, mobility, received signal strength},
	pages = {2215--2220},
}

With the proliferation of mobile devices such as smartphones, an interesting problem is how to make use them to improve the accuracy of localization in indoor environments. In this paper, we develop a novel cooperative localization scheme exploiting mobility in the indoor environment. The problem is formulated as a semidefinite program (SDP) using Linear Matrix Inequality (LMI). With the proposed approach, mobile users utilize their top RSS measurements for distance estimation and to mitigate the the shadowing effect found in indoor environments. In addition, we utilize the estimated position for a user from the last time slot as a virtual access point (AP) to obtain the next position estimation, by utilizing the inertial measurement unit (IMU) data from smartphones. To better take advantage of the moving direction and velocity information provided by the smartphones, we next apply Kalman filter to further mitigate the errors in estimated positions. Simulation results confirm that both the mean error and variance can be effectively reduced by exploiting IMU data and Kalman filter.

@inproceedings{bitner_multipath_2015,
	title = {Multipath and {Spoofing} {Detection} {Using} {Angle} of {Arrival} in a {Multi}-{Antenna} {System}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=12651},
	abstract = {This paper presents and validates a proposed algorithm for the detection and exclusion of erroneous GPS signals using angle of arrival (AOA) of GPS signals and differential carrier phase measurements. First, the attitude of the instrumented vehicle is estimated using a multi-antenna GPS receiver. Once an attitude estimate has been established, it can be propagated forward between GPS measurements using an IMU in a GPS/INS extended Kalman filter (EKF). New measurements may then be checked for angle of arrival, with accepted measurements used to further estimate position and attitude. New attitude estimates are then propagated forward to repeat the checking stage of the algorithm. Results show that the proposed algorithm is a viable method of rejecting signals. Rejected signals are verified as multipath by plotting positioning solutions before and after signal removal on a map of the area the data was taken. Rejected signals are also verified by comparing the expected and measured pseudorange measurements over the periods of time before, during, and after a signal is rejected.},
	language = {en},
	urldate = {2024-06-20},
	author = {Bitner, Thomas and Preston, Sarah and Bevly, David},
	month = jan,
	year = {2015},
	pages = {822--832},
}

This paper presents and validates a proposed algorithm for the detection and exclusion of erroneous GPS signals using angle of arrival (AOA) of GPS signals and differential carrier phase measurements. First, the attitude of the instrumented vehicle is estimated using a multi-antenna GPS receiver. Once an attitude estimate has been established, it can be propagated forward between GPS measurements using an IMU in a GPS/INS extended Kalman filter (EKF). New measurements may then be checked for angle of arrival, with accepted measurements used to further estimate position and attitude. New attitude estimates are then propagated forward to repeat the checking stage of the algorithm. Results show that the proposed algorithm is a viable method of rejecting signals. Rejected signals are verified as multipath by plotting positioning solutions before and after signal removal on a map of the area the data was taken. Rejected signals are also verified by comparing the expected and measured pseudorange measurements over the periods of time before, during, and after a signal is rejected.

@inproceedings{pierce_centralized_2015,
	title = {A {Centralized} {Approach} to {Pedestrian} {Localization} {Using} {Multiple} {Odometry} {Sources}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=12607},
	abstract = {A method is presented for pedestrian localization by use of stereo visual odometry and a foot-mounted inertial navigation system (INS). As opposed to prior approaches for fusing such systems, a centralized model combines the state vector for both visual odometry and INS mechanization using an Extended Kalman Filter (EKF) framework. Correlations are maintained in the centralized filter by pseudo-measurements relating the position and heading of the two systems. Gait monitoring is performed in order to detect vertical leg conditions in which the two systems can be related by a baseline separation. In addition, zero velocity updates are applied to foot velocity states to estimate INS errors. External measurements are applied through a standard EKF update, and their effect on filter performance is shown. Results are presented using both simulated and real data.},
	language = {en},
	urldate = {2024-06-20},
	author = {Pierce, J. Daniel and Bevly, David M.},
	month = jan,
	year = {2015},
	pages = {123--128},
}

A method is presented for pedestrian localization by use of stereo visual odometry and a foot-mounted inertial navigation system (INS). As opposed to prior approaches for fusing such systems, a centralized model combines the state vector for both visual odometry and INS mechanization using an Extended Kalman Filter (EKF) framework. Correlations are maintained in the centralized filter by pseudo-measurements relating the position and heading of the two systems. Gait monitoring is performed in order to detect vertical leg conditions in which the two systems can be related by a baseline separation. In addition, zero velocity updates are applied to foot velocity states to estimate INS errors. External measurements are applied through a standard EKF update, and their effect on filter performance is shown. Results are presented using both simulated and real data.

@inproceedings{carson_robust_2015,
	title = {A {Robust} {Method} for {Spoofing} {Prevention} and {Position} {Recovery} in {Attacks} against {Networked} {GPS} {Receivers}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=12689},
	abstract = {With the growing level of dependence on the Global Positioning System (GPS), it is critical to protect its integrity and ensure its robustness against a variety of threats. Until recent years, knowledge of the structure, operation, and technologies behind GPS was not extensively available in civilian arenas. But the growing popularity of GPS has led to increased public knowledge of its operating principles. Along with increased use has come a variety of threats. Due to the structure of the GPS signal and its relative weakness compared to local background noise, GPS is susceptible to both jamming and spoofing attacks. Jamming operates by blanketing a region in GPS frequency noise to prevent receivers from detecting authentic signals. Spoofing is a more sophisticated method of attack in which receivers are deceived into tracking false signals and calculating an incorrect position solution. Methods of detecting such attacks have been researched on several fronts mostly in the signals processing arena where signal power and other parameters can provide indications of spoofing [1]. This paper presents a spoofing prevention method which provides a way to detect, identify, and mitigate a spoofing attack on a networked GPS receiver. The method uses ranging information between nodes to detect anomalies that indicate spoofing of the GPS positions. Signal parameters of the attacking signal are extracted by tracking loops designated to the spoofed signal. Using these parameters, the encroaching signal is removed in the IF stage by a successive interference cancelation (SIC) method. This anti-spoofing routine has an advantage over other methods due to its robustness in a wide variety of situations combined with its ability to mitigate an attack without any prior knowledge of the spoofer or the spoofed signal characteristics.},
	language = {en},
	urldate = {2024-06-20},
	author = {Carson, Nathaniel and Bevly, David},
	month = jan,
	year = {2015},
	pages = {623--632},
}

With the growing level of dependence on the Global Positioning System (GPS), it is critical to protect its integrity and ensure its robustness against a variety of threats. Until recent years, knowledge of the structure, operation, and technologies behind GPS was not extensively available in civilian arenas. But the growing popularity of GPS has led to increased public knowledge of its operating principles. Along with increased use has come a variety of threats. Due to the structure of the GPS signal and its relative weakness compared to local background noise, GPS is susceptible to both jamming and spoofing attacks. Jamming operates by blanketing a region in GPS frequency noise to prevent receivers from detecting authentic signals. Spoofing is a more sophisticated method of attack in which receivers are deceived into tracking false signals and calculating an incorrect position solution. Methods of detecting such attacks have been researched on several fronts mostly in the signals processing arena where signal power and other parameters can provide indications of spoofing [1]. This paper presents a spoofing prevention method which provides a way to detect, identify, and mitigate a spoofing attack on a networked GPS receiver. The method uses ranging information between nodes to detect anomalies that indicate spoofing of the GPS positions. Signal parameters of the attacking signal are extracted by tracking loops designated to the spoofed signal. Using these parameters, the encroaching signal is removed in the IF stage by a successive interference cancelation (SIC) method. This anti-spoofing routine has an advantage over other methods due to its robustness in a wide variety of situations combined with its ability to mitigate an attack without any prior knowledge of the spoofer or the spoofed signal characteristics.

@unpublished{jantz_development_2014,
	type = {thesis},
	title = {Development of a {Multi}-mode {Adaptive} {Controller} and {Investigation} of {Gain} {Variations} with {Speed} and {Balance} {Changes}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/4002},
	abstract = {Magnetic bearings offer a number of advantages over conventional rolling element bearings. Magnetic bearings provide support for rotating systems through magnetic levitation rather than by mechanical contact, nearly eliminating the energy losses attributable to friction in standard bearings. Low power consumption is one characteristic of magnetic bearings that has encouraged their use in an increasing number of applications. Another is the ability to use the bearing itself as an actuator in a controller that can alter the orbit of the rotating system within the bearing to reduce or eliminate the detrimental effects of disturbances acting on the system. In addition, controller outputs can potentially be used as an indicator of the general health or integrity of the system.
This work details the development of a multi-mode adaptive controller for a magnetic bearing system that is capable of suppressing disturbances acting at synchronous and asynchronous frequencies and caused by rotating imbalances and base motion. The work was based on an existing adaptive controller that formed part of the overall control system for a well sorted and well developed magnetically suspended rotor and flywheel. The development of the controller made extensive use of system modeling techniques and model-in-the-loop simulations. Development also required continual refinement of the system model and on-going reconfiguration of the operating environment since the ever increasing complexity of the controller often exceeded the real-time capabilities of the processor.
The modes of the controller, or the methods used by it to determine the frequency of the disturbance acting on the system, include discrete Fourier transform, rotor speed and manual observation. The adaptive controller was shown to produce excellent disturbance rejection and vibration suppression in all of the three modes. The capabilities of the controller operating in the first mode were demonstrated with simulated disturbances and in the second and third modes with software simulations, simulated disturbances and physical changes in the balance of the rotor and flywheel.
This work also details the efforts to evaluate the predictive capability of adaptive controller gains. The correlation between gain variations and balance state has been demonstrated, but a repeatable and unambiguous response of the gains to a synchronous disturbance undetectable by other means has not been well established. The sensitivity of the gains to variations in rotor speed increases the difficulty of this task. Software simulations of the adaptive controller operating in speed mode showed the potential of using the gains as an indicator of a change in the balance or health of the system, but actual tests conducted on the magnetic bearing system were not as encouraging.},
	language = {en},
	urldate = {2024-06-25},
	author = {Jantz, James},
	month = mar,
	year = {2014},
	note = {Accepted: 2014-03-20T18:49:28Z},
}

Magnetic bearings offer a number of advantages over conventional rolling element bearings. Magnetic bearings provide support for rotating systems through magnetic levitation rather than by mechanical contact, nearly eliminating the energy losses attributable to friction in standard bearings. Low power consumption is one characteristic of magnetic bearings that has encouraged their use in an increasing number of applications. Another is the ability to use the bearing itself as an actuator in a controller that can alter the orbit of the rotating system within the bearing to reduce or eliminate the detrimental effects of disturbances acting on the system. In addition, controller outputs can potentially be used as an indicator of the general health or integrity of the system. This work details the development of a multi-mode adaptive controller for a magnetic bearing system that is capable of suppressing disturbances acting at synchronous and asynchronous frequencies and caused by rotating imbalances and base motion. The work was based on an existing adaptive controller that formed part of the overall control system for a well sorted and well developed magnetically suspended rotor and flywheel. The development of the controller made extensive use of system modeling techniques and model-in-the-loop simulations. Development also required continual refinement of the system model and on-going reconfiguration of the operating environment since the ever increasing complexity of the controller often exceeded the real-time capabilities of the processor. The modes of the controller, or the methods used by it to determine the frequency of the disturbance acting on the system, include discrete Fourier transform, rotor speed and manual observation. The adaptive controller was shown to produce excellent disturbance rejection and vibration suppression in all of the three modes. The capabilities of the controller operating in the first mode were demonstrated with simulated disturbances and in the second and third modes with software simulations, simulated disturbances and physical changes in the balance of the rotor and flywheel. This work also details the efforts to evaluate the predictive capability of adaptive controller gains. The correlation between gain variations and balance state has been demonstrated, but a repeatable and unambiguous response of the gains to a synchronous disturbance undetectable by other means has not been well established. The sensitivity of the gains to variations in rotor speed increases the difficulty of this task. Software simulations of the adaptive controller operating in speed mode showed the potential of using the gains as an indicator of a change in the balance or health of the system, but actual tests conducted on the magnetic bearing system were not as encouraging.

@unpublished{hennigar_analysis_2014,
	type = {thesis},
	title = {Analysis of {Record} and {Playback} {Errors} of {GPS} {Signals} {Caused} by the {USRP}},
	url = {https://etd.auburn.edu//handle/10415/4442},
	abstract = {In this thesis, the errors created by the USRP (Universal Software Receiver Platform) during record and playback are analyzed. The USRP is used for jamming, spoo fing, and
GPS processing, and has recently become widely used for capturing GPS signals for record and playback. However, there has been little research into how the USRP e ffects signal
quality during record and playback.

This thesis is based on the live capture of L1 GPS signals. Data is captured for multiple scenarios in both static and dynamic situations. The signal is split and sent to multiple
receivers and the USRP. The data is gathered, parsed, and quantifi ed using statistical analysis for comparison over a broad range of tests.

From the captured signals, statistical analysis is used for a more comprehensive overview of the USRP. Results show that statistical data from playback of GPS signals is reliable in
multiple scenarios, thus validation the USRP as an accurate means by which data can be recorded and played back.},
	language = {en},
	urldate = {2024-06-25},
	author = {Hennigar, Andrew},
	month = dec,
	year = {2014},
	note = {Accepted: 2014-12-10T20:36:52Z},
}

In this thesis, the errors created by the USRP (Universal Software Receiver Platform) during record and playback are analyzed. The USRP is used for jamming, spoo fing, and GPS processing, and has recently become widely used for capturing GPS signals for record and playback. However, there has been little research into how the USRP e ffects signal quality during record and playback. This thesis is based on the live capture of L1 GPS signals. Data is captured for multiple scenarios in both static and dynamic situations. The signal is split and sent to multiple receivers and the USRP. The data is gathered, parsed, and quantifi ed using statistical analysis for comparison over a broad range of tests. From the captured signals, statistical analysis is used for a more comprehensive overview of the USRP. Results show that statistical data from playback of GPS signals is reliable in multiple scenarios, thus validation the USRP as an accurate means by which data can be recorded and played back.

@unpublished{colbert_development_2014,
	type = {thesis},
	title = {Development of a {Custom} {Data} {Acquisition} {System} for the {Study} of {Vehicle} {Dynamics} in {Longer} {Combination} {Vehicles}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/4262},
	abstract = {This thesis details the development, deployment, and verification of a custom data acquisition system for the purpose of studying vehicle dynamics in a triple trailer Longer Combination Vehicle (LCV). In addition to the data acquisition the thesis details the simulation efforts that were undertaken to both verify the experimental data as well as assess the stability of the vehicle itself. The research was part of an effort to assess the viability of widening the available roadways that are currently accessible to LCV trailers. This project undertook the task of fully instrumenting a triple trailer LCV with a package of more than 35 sensors and implementation of a custom Data Acquisition System (DAQ) to log over 200 channels coming from the aforementioned sensors. Once outfitted with the sensor package, the LCV was put through a variety of dynamic tests including lane changes and constant radius turns in an attempt to capture various dynamic characteristics of the vehicle. 

A series of simulations were run to match the maneuvers undertaken during the experimental phase. That data was then compared to ensure that the simulation did indeed agree with the experimental data. Once in agreement the simulations were expanded to speeds that were not able to be achieved experimentally due to safety concerns. The last element of the simulation was a comparison between the LCV triple and a standard double trailer heavy truck as seen on the highways today. 

The LCV under test behaved as expected given the prior research into LCV dynamics. Additionally the simulation and the experimental data were shown to agree. The simulation exposed the instability of the vehicle at speeds easily expected on the highways. When comparing the triple LCV to the double it was shown that at lower speeds the first four units behaved similarly, but as the speeds increased the effects of the third trailer were shown in the responses of the second. Finally this thesis shows that there is a need for heavy precautions before allowing triple LCV to traverse the highway roads. At lower speeds the vehicle is safe but increasing that speed to that of the standard highway speed shows that the vehicle will respond with undesirable outputs.},
	language = {en},
	urldate = {2024-06-25},
	author = {Colbert, Jameson},
	month = jul,
	year = {2014},
	note = {Accepted: 2014-07-11T15:42:01Z},
}

This thesis details the development, deployment, and verification of a custom data acquisition system for the purpose of studying vehicle dynamics in a triple trailer Longer Combination Vehicle (LCV). In addition to the data acquisition the thesis details the simulation efforts that were undertaken to both verify the experimental data as well as assess the stability of the vehicle itself. The research was part of an effort to assess the viability of widening the available roadways that are currently accessible to LCV trailers. This project undertook the task of fully instrumenting a triple trailer LCV with a package of more than 35 sensors and implementation of a custom Data Acquisition System (DAQ) to log over 200 channels coming from the aforementioned sensors. Once outfitted with the sensor package, the LCV was put through a variety of dynamic tests including lane changes and constant radius turns in an attempt to capture various dynamic characteristics of the vehicle. A series of simulations were run to match the maneuvers undertaken during the experimental phase. That data was then compared to ensure that the simulation did indeed agree with the experimental data. Once in agreement the simulations were expanded to speeds that were not able to be achieved experimentally due to safety concerns. The last element of the simulation was a comparison between the LCV triple and a standard double trailer heavy truck as seen on the highways today. The LCV under test behaved as expected given the prior research into LCV dynamics. Additionally the simulation and the experimental data were shown to agree. The simulation exposed the instability of the vehicle at speeds easily expected on the highways. When comparing the triple LCV to the double it was shown that at lower speeds the first four units behaved similarly, but as the speeds increased the effects of the third trailer were shown in the responses of the second. Finally this thesis shows that there is a need for heavy precautions before allowing triple LCV to traverse the highway roads. At lower speeds the vehicle is safe but increasing that speed to that of the standard highway speed shows that the vehicle will respond with undesirable outputs.

@unpublished{williams_evaluation_2014,
	type = {thesis},
	title = {Evaluation of {Beam} {Load} {Cell} {Use} for {Base} {Reaction} {Force} {Collision} {Detection} on {Industrial} {Robots}},
	url = {https://etd.auburn.edu//handle/10415/4355},
	abstract = {This thesis evaluates the ability of four beam load cells placed under the base of an industrial robot to accurately estimate robot link parameters and detect collision. This setup can be a cheaper option than using six-degree-of-freedom sensors, and is easier to implement than other detection methods. The beam load cells are placed under the base of robotic manipulators, and the reactions at the base of the robot due to its motion can be monitored to detect collision and estimate link parameters. The tradeoff to using only four load cells is a more limited ability to sense the reaction forces and moments.

The results of this research show that the method of using beam load cells, despite the limited ability to measure base reactions, was able to reduce parameter estimation error from 1,475 to 432Nm, or in terms of percentage from 28\% to 8\%. Furthermore, this method is capable of detecting collisions; however, the accuracy of parameter estimation and collision detection is limited by sensor noise and large amplitude vibrations in the tested robot system.},
	language = {en},
	urldate = {2024-06-25},
	author = {Williams, Robert},
	month = oct,
	year = {2014},
	note = {Accepted: 2014-10-10T21:03:51Z},
}

This thesis evaluates the ability of four beam load cells placed under the base of an industrial robot to accurately estimate robot link parameters and detect collision. This setup can be a cheaper option than using six-degree-of-freedom sensors, and is easier to implement than other detection methods. The beam load cells are placed under the base of robotic manipulators, and the reactions at the base of the robot due to its motion can be monitored to detect collision and estimate link parameters. The tradeoff to using only four load cells is a more limited ability to sense the reaction forces and moments. The results of this research show that the method of using beam load cells, despite the limited ability to measure base reactions, was able to reduce parameter estimation error from 1,475 to 432Nm, or in terms of percentage from 28% to 8%. Furthermore, this method is capable of detecting collisions; however, the accuracy of parameter estimation and collision detection is limited by sensor noise and large amplitude vibrations in the tested robot system.

@unpublished{wang_robust_2014,
	title = {Robust {Gain}-{Scheduled} {Observer} {Design} with {Application} to {Vehicle} {State} {Estimation}},
	url = {https://etd.auburn.edu//handle/10415/4351},
	abstract = {This dissertation develops an application of the state-of-the-art convex optimization algorithms to the vehicle state estimation problem. The main challenge in this field is that the time-varying uncertain parameters and nonlinearity are both contained in the vehicle dynamical models. In the automotive control systems products, the gain-scheduled control and estimation algorithms are widely used to deal with these difficult components. However, the tuning of the stable controller and observer parameters is a heuristic and time-consuming task. A vast amount of simulation and validation experiments have to be implemented to verify the performance of the algorithm. Sometimes, the trial-and-error cycle is inevitable. Therefore, an efficient gain-scheduled observer design methodology for both linear and nonlinear systems is the main topic of this dissertation. 

First, the linear-parameter-varying (LPV) representation of the three degree-of-freedom (DOF) bicycle model is presented, where the longitudinal velocity and acceleration are treated as the online measurable time-varying parameters. The LPV design methodology overcomes some eminent drawbacks of the traditional gain scheduled design methods. In the LPV framework, the search of the globally convergent observer parameters are resorted to a semidefinite programming problem. It is also shown that some robust controller design methods can be applied to develop an optimal unstructured LPV observer.

Next, the LPV observer is extended to a gain-scheduled interval observer where the variation range of the uncertain cornering stiffness parameters is incorporated into the observer design. Instead of a single estimation curve for each state variable, the interval observer computes the lower and upper bounds of all the admissible values of the states in the presence of parametric uncertainty. For automotive active safety systems, this envelope provides an estimation of the worst case bounds for the critical vehicle state under uncertain road conditions. 

Although the gain-scheduled interval observer directly takes the uncertain cornering stiffness parameters into consideration, the tire-road friction is a highly complex nonlinear phenomenon such that the linear observer is far from satisfactory in some extreme maneuvers. To further improve the performance of the estimation algorithm, a nonlinear observer design methodology is also developed for a class of differentiable Lipschitz continuous nonlinear systems. Since the nonlinear bicycle model also contains the time-varying parameters, the time invariant nonlinear observer is further augmented to a gain scheduled nonlinear observer.

The simulation results demonstrate the validity of the proposed gain-scheduled observer design to provide accurate and robust estimation of vehicle states, such as tire slip angles in the presence of time-varying parameters and nonlinearities.

All the vehicle state estimation algorithms proposed in this dissertation are verified by using the simulation data from CarSim, a commercial vehicle simulation software package. Additionally, all the observer design methodologies are formulated in a high-level systematic approach, which allow them to be applied to other systems.},
	language = {en},
	urldate = {2024-06-25},
	author = {Wang, Yan},
	month = oct,
	year = {2014},
	note = {Accepted: 2014-10-10T20:55:38Z},
}

This dissertation develops an application of the state-of-the-art convex optimization algorithms to the vehicle state estimation problem. The main challenge in this field is that the time-varying uncertain parameters and nonlinearity are both contained in the vehicle dynamical models. In the automotive control systems products, the gain-scheduled control and estimation algorithms are widely used to deal with these difficult components. However, the tuning of the stable controller and observer parameters is a heuristic and time-consuming task. A vast amount of simulation and validation experiments have to be implemented to verify the performance of the algorithm. Sometimes, the trial-and-error cycle is inevitable. Therefore, an efficient gain-scheduled observer design methodology for both linear and nonlinear systems is the main topic of this dissertation. First, the linear-parameter-varying (LPV) representation of the three degree-of-freedom (DOF) bicycle model is presented, where the longitudinal velocity and acceleration are treated as the online measurable time-varying parameters. The LPV design methodology overcomes some eminent drawbacks of the traditional gain scheduled design methods. In the LPV framework, the search of the globally convergent observer parameters are resorted to a semidefinite programming problem. It is also shown that some robust controller design methods can be applied to develop an optimal unstructured LPV observer. Next, the LPV observer is extended to a gain-scheduled interval observer where the variation range of the uncertain cornering stiffness parameters is incorporated into the observer design. Instead of a single estimation curve for each state variable, the interval observer computes the lower and upper bounds of all the admissible values of the states in the presence of parametric uncertainty. For automotive active safety systems, this envelope provides an estimation of the worst case bounds for the critical vehicle state under uncertain road conditions. Although the gain-scheduled interval observer directly takes the uncertain cornering stiffness parameters into consideration, the tire-road friction is a highly complex nonlinear phenomenon such that the linear observer is far from satisfactory in some extreme maneuvers. To further improve the performance of the estimation algorithm, a nonlinear observer design methodology is also developed for a class of differentiable Lipschitz continuous nonlinear systems. Since the nonlinear bicycle model also contains the time-varying parameters, the time invariant nonlinear observer is further augmented to a gain scheduled nonlinear observer. The simulation results demonstrate the validity of the proposed gain-scheduled observer design to provide accurate and robust estimation of vehicle states, such as tire slip angles in the presence of time-varying parameters and nonlinearities. All the vehicle state estimation algorithms proposed in this dissertation are verified by using the simulation data from CarSim, a commercial vehicle simulation software package. Additionally, all the observer design methodologies are formulated in a high-level systematic approach, which allow them to be applied to other systems.

@inproceedings{berkemeier_suitability_2014,
	title = {On the suitability of {Nonlinear} {Model} {Predictive} {Control} for {Unmanned} {Ground} {Vehicles}},
	url = {https://ieeexplore.ieee.org/abstract/document/6858827},
	doi = {10.1109/ACC.2014.6858827},
	abstract = {Nonlinear Model Predictive Control (NMPC) has great appeal for vehicle path control due to its ability to easily handle nonlinear dynamic models with constraints while achieving near-optimal control. The drawback is that a straight-forward application results in computations that take too long for real-time use. In this paper, we explore these issues in the use of NMPC for vehicle control. Methods for speeding up the computations are discussed.},
	urldate = {2024-06-20},
	booktitle = {2014 {American} {Control} {Conference}},
	author = {Berkemeier, Matthew D. and Perez, Sostenes and Bevly, David},
	month = jun,
	year = {2014},
	note = {ISSN: 2378-5861},
	keywords = {Automotive, Cost function, Mathematical model, Portable computers, Predictive control, Predictive control for nonlinear systems, Trajectory, Vehicles},
	pages = {4605--4610},
}

Nonlinear Model Predictive Control (NMPC) has great appeal for vehicle path control due to its ability to easily handle nonlinear dynamic models with constraints while achieving near-optimal control. The drawback is that a straight-forward application results in computations that take too long for real-time use. In this paper, we explore these issues in the use of NMPC for vehicle control. Methods for speeding up the computations are discussed.

@inproceedings{hennigar_error_2014,
	title = {Error analysis of {GPS} signals from {USRP} using {GPS} receivers},
	url = {https://ieeexplore.ieee.org/document/6851472/;jsessionid=8277C76A1ECF43EBD0C2E9F3EEF84A2B},
	doi = {10.1109/PLANS.2014.6851472},
	abstract = {In this paper the USRP (Universal Software Radio Peripheral) will be explored to characterize GPS receivers. The main receiver will be the Ublox receiver. The errors added to the recorded signals, by the USRP, will also be quantified and analyzed in order to observe any trends. These trends will then be compared to known models to validate the type of error seen. This paper hopes to expand the uses of the USRP, and validate its use as an acceptable, convenient tool for processing GPS data. The paper will also give a better understanding of the errors inserted by the USRP.},
	urldate = {2024-06-20},
	booktitle = {2014 {IEEE}/{ION} {Position}, {Location} and {Navigation} {Symposium} - {PLANS} 2014},
	author = {Hennigar, Andrew and Bevly, David M.},
	month = may,
	year = {2014},
	note = {ISSN: 2153-3598},
	keywords = {Global Positioning System, Market research, Mathematical model, Noise, Receivers, Standards, Timing},
	pages = {1041--1047},
}

In this paper the USRP (Universal Software Radio Peripheral) will be explored to characterize GPS receivers. The main receiver will be the Ublox receiver. The errors added to the recorded signals, by the USRP, will also be quantified and analyzed in order to observe any trends. These trends will then be compared to known models to validate the type of error seen. This paper hopes to expand the uses of the USRP, and validate its use as an acceptable, convenient tool for processing GPS data. The paper will also give a better understanding of the errors inserted by the USRP.

@inproceedings{salmon_exploration_2014,
	title = {An exploration of low-cost sensor and vehicle model {Solutions} for ground vehicle navigation},
	url = {https://ieeexplore.ieee.org/document/6851404/;jsessionid=0A17548556ACA61DCD2CB2A90A28E249},
	doi = {10.1109/PLANS.2014.6851404},
	abstract = {This paper discusses an exploratory analyses of the benefits of using Vehicle Odometry/Steer Angle and an accurate vehicle model (VM) to replace/assist a low-cost Inertial Measurement Unit (IMU) for blended ground vehicle navigation. In this research, multiple variations of the tightly coupled Extended Kalman Filter (EKF) algorithm are performed using multiple sensor sets to find the optimal solution, factoring in sensor cost and pose accuracy. Many automotive precision navigation solutions have been developed based on sensor fusion in recent years; however, as autonomous navigation technology becomes more prevalent on consumer vehicles, the need for a high-accuracy, low-cost pose solution is increasing. One widely used solution to this problem is the combination of a Micro-Electro-Mechanical (MEMS) IMU with Global Positioning System (GPS); however, this may not be the optimal solution due to the high noise characteristics of lower cost IMU's. Measurements from GPS, IMU/Inertial Navigation System (INS), and VM are used in this research. The different algorithm setups being investigated include: GPS/VM sensor fusion with accurate vehicle model constraints, GPS/INS with low-cost commercially available IMU, and GPS/INS/VM with the IMU. The determination of the level of IMU necessary for GPS/INS fusion to exceed the pose solution accuracy achievable using GPS/VM sensor fusion with accurate vehicle model constraints is a priority for this research. Another goal of this research is the quantitative and qualitative analysis of the benefits of using VM to assist normal GPS/INS EKF and whether the inclusion of VM in either the time update or the measurement update results in a more accurate pose solution. Direct experimental comparison of tightly coupled EKF Fault Detection and Exclusion (FDE) algorithms based on vehicle wheel speed and steering angle versus the IMU measurements to determine if either sensor set yields a distinct advantage over the other is also investigated. All analysis will be based on real world experimental data.},
	urldate = {2024-06-20},
	booktitle = {2014 {IEEE}/{ION} {Position}, {Location} and {Navigation} {Symposium} - {PLANS} 2014},
	author = {Salmon, Daniel C. and Bevly, David M.},
	month = may,
	year = {2014},
	note = {ISSN: 2153-3598},
	keywords = {Dynamic Vehicle Model, Global Positioning System, Kalman filters, Mathematical model, Sensor Fused Navigation, Tightly Coupled Extended Kalman Filter, Vehicle Odometry, Vehicle dynamics, Vehicles, Wheels},
	pages = {462--471},
}

This paper discusses an exploratory analyses of the benefits of using Vehicle Odometry/Steer Angle and an accurate vehicle model (VM) to replace/assist a low-cost Inertial Measurement Unit (IMU) for blended ground vehicle navigation. In this research, multiple variations of the tightly coupled Extended Kalman Filter (EKF) algorithm are performed using multiple sensor sets to find the optimal solution, factoring in sensor cost and pose accuracy. Many automotive precision navigation solutions have been developed based on sensor fusion in recent years; however, as autonomous navigation technology becomes more prevalent on consumer vehicles, the need for a high-accuracy, low-cost pose solution is increasing. One widely used solution to this problem is the combination of a Micro-Electro-Mechanical (MEMS) IMU with Global Positioning System (GPS); however, this may not be the optimal solution due to the high noise characteristics of lower cost IMU's. Measurements from GPS, IMU/Inertial Navigation System (INS), and VM are used in this research. The different algorithm setups being investigated include: GPS/VM sensor fusion with accurate vehicle model constraints, GPS/INS with low-cost commercially available IMU, and GPS/INS/VM with the IMU. The determination of the level of IMU necessary for GPS/INS fusion to exceed the pose solution accuracy achievable using GPS/VM sensor fusion with accurate vehicle model constraints is a priority for this research. Another goal of this research is the quantitative and qualitative analysis of the benefits of using VM to assist normal GPS/INS EKF and whether the inclusion of VM in either the time update or the measurement update results in a more accurate pose solution. Direct experimental comparison of tightly coupled EKF Fault Detection and Exclusion (FDE) algorithms based on vehicle wheel speed and steering angle versus the IMU measurements to determine if either sensor set yields a distinct advantage over the other is also investigated. All analysis will be based on real world experimental data.

@inproceedings{wang_observer_2014,
	title = {Observer design for differentiable {Lipschitz} nonlinear systems with time-varying parameters},
	url = {https://ieeexplore.ieee.org/document/7039373/;jsessionid=67A81C205068D4FBC032922711F83385},
	doi = {10.1109/CDC.2014.7039373},
	abstract = {This paper develops observer design techniques in a unified framework for both time invariant and parameter varying Lipschitz nonlinear systems that are differentiable w.r.t. state variables. First, a new sufficient condition for asymptotic convergence is developed for both the extended Luenberger observer and a two-DOF nonlinear observer for time-invariant nonlinear systems. In addition to ensuring asymptotic convergence, extension of this observer design technique to optimization of a L2 performance criterion is presented, which enables the observer to handle the unknown disturbance inputs as well as ensure robustness to model uncertainty. Next, augmentation of this technique to parameter varying nonlinear (PVNL) systems is developed. Different from methods suggested in the LPV literature, a simple but non-conservative finite dimensional relaxation method for quadratic parameter dependent LMIs is presented. These results constitute perhaps the first systematic observer design methodology in literature for PVNL systems. Finally, a simulation result for vehicle slip angle estimation is presented to verify the performance of the developed observer design methods.},
	urldate = {2024-06-20},
	booktitle = {53rd {IEEE} {Conference} on {Decision} and {Control}},
	author = {Wang, Yan and Rajamani, Rajesh and Bevly, David M.},
	month = dec,
	year = {2014},
	note = {ISSN: 0191-2216},
	keywords = {Convergence, Jacobian matrices, Linear matrix inequalities, Nonlinear systems, Observers, Time-varying systems, Upper bound},
	pages = {145--152},
}

This paper develops observer design techniques in a unified framework for both time invariant and parameter varying Lipschitz nonlinear systems that are differentiable w.r.t. state variables. First, a new sufficient condition for asymptotic convergence is developed for both the extended Luenberger observer and a two-DOF nonlinear observer for time-invariant nonlinear systems. In addition to ensuring asymptotic convergence, extension of this observer design technique to optimization of a L2 performance criterion is presented, which enables the observer to handle the unknown disturbance inputs as well as ensure robustness to model uncertainty. Next, augmentation of this technique to parameter varying nonlinear (PVNL) systems is developed. Different from methods suggested in the LPV literature, a simple but non-conservative finite dimensional relaxation method for quadratic parameter dependent LMIs is presented. These results constitute perhaps the first systematic observer design methodology in literature for PVNL systems. Finally, a simulation result for vehicle slip angle estimation is presented to verify the performance of the developed observer design methods.

@inproceedings{bishop_results_2014,
	title = {Results of initial test and evaluation of a {Driver}-{Assistive} {Truck} {Platooning} prototype},
	url = {https://ieeexplore.ieee.org/document/6856585/;jsessionid=9C1A01C3BB065FC2CBC71617F01B9348},
	doi = {10.1109/IVS.2014.6856585},
	abstract = {This paper describes results to date of a project to prototype, evaluate, and test Driver-Assistive Truck Platooning (DATP), which could have significant positive safety and fuel savings potential for heavy truck operations. The project is led by Auburn University and funded within the Federal Highway Administration Exploratory Advanced Research program. This paper provides selected results from Phase One, which is currently exploring a range of technical and non-technical issues, including assessing real-world business and operational issues within the trucking industry. Specific technical sections address sensing and computing hardware; driver interface; sensor and actuator software and interfacing; control software; and operational environment.},
	urldate = {2024-06-20},
	booktitle = {2014 {IEEE} {Intelligent} {Vehicles} {Symposium} {Proceedings}},
	author = {Bishop, Richard and Bevly, David and Switkes, Joshua and Park, Lisa},
	month = jun,
	year = {2014},
	note = {ISSN: 1931-0587},
	keywords = {Fuels, Industries, Joining processes, Roads, Safety, Vehicles},
	pages = {208--213},
}

This paper describes results to date of a project to prototype, evaluate, and test Driver-Assistive Truck Platooning (DATP), which could have significant positive safety and fuel savings potential for heavy truck operations. The project is led by Auburn University and funded within the Federal Highway Administration Exploratory Advanced Research program. This paper provides selected results from Phase One, which is currently exploring a range of technical and non-technical issues, including assessing real-world business and operational issues within the trucking industry. Specific technical sections address sensing and computing hardware; driver interface; sensor and actuator software and interfacing; control software; and operational environment.

@article{rose_integrated_2014,
	title = {An {Integrated} {Vehicle} {Navigation} {System} {Utilizing} {Lane}-{Detection} and {Lateral} {Position} {Estimation} {Systems} in {Difficult} {Environments} for {GPS}},
	volume = {15},
	issn = {1558-0016},
	url = {https://ieeexplore.ieee.org/document/6822610/;jsessionid=42809654FABB8393AAD6EA28E0658F60},
	doi = {10.1109/TITS.2014.2321108},
	abstract = {A navigation filter combines measurements from sensors currently available on vehicles - Global Positioning System (GPS), inertial measurement unit, inertial measurement unit (IMU), camera, and light detection and ranging (lidar) - for achieving lane-level positioning in environments where stand-alone GPS can suffer or fail. Measurements from the camera and lidar are used in two lane-detection systems, and the calculated lateral distance (to the lane markings) estimates of both lane-detection systems are compared with centimeter-level truth to show decimeter-level accuracy. The navigation filter uses the lateral distance measurements from the lidar- and camera-based systems with a known waypoint-based map to provide global measurements for use in a GPS/Inertial Navigation System (INS) system. Experimental results show that the inclusion of lateral distance measurements and a height constraint from the map creates a fully observable system even with only two satellite observations and, as such, greatly enhances the robustness of the integrated system over GPS/INS alone. Various scenarios are presented, which affect the navigation filter, including satellite geometry, number of satellites, and loss of lateral distance measurements from the camera and lidar systems.},
	number = {6},
	urldate = {2024-06-20},
	journal = {IEEE Transactions on Intelligent Transportation Systems},
	author = {Rose, Christopher and Britt, Jordan and Allen, John and Bevly, David},
	month = dec,
	year = {2014},
	keywords = {Camera, Cameras, Global Navigation Satellite System, Global Positioning System, Global Positioning System (GPS), Image edge detection, Kalman filter, Kalman filters, Sensor fusion, inertial measurement unit (IMU), lane detection, light detection and ranging (lidar), outages, sensor fusion},
	pages = {2615--2629},
}

A navigation filter combines measurements from sensors currently available on vehicles - Global Positioning System (GPS), inertial measurement unit, inertial measurement unit (IMU), camera, and light detection and ranging (lidar) - for achieving lane-level positioning in environments where stand-alone GPS can suffer or fail. Measurements from the camera and lidar are used in two lane-detection systems, and the calculated lateral distance (to the lane markings) estimates of both lane-detection systems are compared with centimeter-level truth to show decimeter-level accuracy. The navigation filter uses the lateral distance measurements from the lidar- and camera-based systems with a known waypoint-based map to provide global measurements for use in a GPS/Inertial Navigation System (INS) system. Experimental results show that the inclusion of lateral distance measurements and a height constraint from the map creates a fully observable system even with only two satellite observations and, as such, greatly enhances the robustness of the integrated system over GPS/INS alone. Various scenarios are presented, which affect the navigation filter, including satellite geometry, number of satellites, and loss of lateral distance measurements from the camera and lidar systems.

@inproceedings{keyser_implementation_2014,
	title = {Implementation {Details} of a {Real}-{Time} {SoC}-{Based} {Vector} {Tracking} {Receiver}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=12429},
	abstract = {This paper shares the implementation details of a real-time vector tracking receiver as constructed on a system-on-chip platform. Vector tracking receivers boast many benefits including the ability to track satellites at low carrier-to-noise (C/N?) ratios and instant reacquisition of satellites after brief outages. While vector tracking receivers offer many benefits, those benefits come at a high computational cost. For that reason, the authors have sought to construct a small, low-cost solution for a vector tracking receiver. The receiver described here takes advantage of the high-speed parallel processing capabilities of an FPGA while incorporating a dual-core ARM processor. This structure helps to overcome many of the difficulties of implementing the vector tracking algorithms in real-time.},
	language = {en},
	urldate = {2024-06-20},
	author = {Keyser, B. and Hodo, D. and Martin, S. and Bevly, D.},
	month = sep,
	year = {2014},
	pages = {1396--1402},
}

This paper shares the implementation details of a real-time vector tracking receiver as constructed on a system-on-chip platform. Vector tracking receivers boast many benefits including the ability to track satellites at low carrier-to-noise (C/N?) ratios and instant reacquisition of satellites after brief outages. While vector tracking receivers offer many benefits, those benefits come at a high computational cost. For that reason, the authors have sought to construct a small, low-cost solution for a vector tracking receiver. The receiver described here takes advantage of the high-speed parallel processing capabilities of an FPGA while incorporating a dual-core ARM processor. This structure helps to overcome many of the difficulties of implementing the vector tracking algorithms in real-time.

@inproceedings{preston_csac-aided_2014,
	title = {{CSAC}-{Aided} {GPS} {Multipath} {Mitigation}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=12588},
	abstract = {This paper introduces a method for GPS multipath mitigation using a chip-scale atomic clock (CSAC). A CSAC provides a stable, accurate timing source to a GPS receiver. Because the clock on a GPS receiver is typically not synchronized to the GPS satellite clocks, there is a difference between the two clocks, which is called a timing bias. Since a typical GPS solution requires solving for 3D position and a timing bias, at least four GPS satellites must be in view to get a time and position solution. Using the CSAC, the initial timing bias will be solved for, and future measurements of the timing bias will be computed. When the measurements exceed a certain threshold, at least one of the satellites in view has been corrupted by multipath. Then a solution involving only fewer satellites than are in view will be solved for. Baseline testing was done in clear sky in an open field at Auburn University. Multipath testing was also done with antennas on a test vehicle in downtown Atlanta, an area known to be an urban canyon with high instances of multipath, as well as around downtown Auburn, where multipath is possible, but not as detrimental as in downtown Atlanta. The algorithm’s ability to navigate using only three satellites Finally, the proposed technique will be compared to other multipath algorithms developed at Auburn University, which include angle-of-arrival (AOA) and carrier-phase residual techniques.},
	language = {en},
	urldate = {2024-06-20},
	author = {Preston, Sarah E. and Bevly, David M.},
	month = dec,
	year = {2014},
	pages = {228--234},
}

This paper introduces a method for GPS multipath mitigation using a chip-scale atomic clock (CSAC). A CSAC provides a stable, accurate timing source to a GPS receiver. Because the clock on a GPS receiver is typically not synchronized to the GPS satellite clocks, there is a difference between the two clocks, which is called a timing bias. Since a typical GPS solution requires solving for 3D position and a timing bias, at least four GPS satellites must be in view to get a time and position solution. Using the CSAC, the initial timing bias will be solved for, and future measurements of the timing bias will be computed. When the measurements exceed a certain threshold, at least one of the satellites in view has been corrupted by multipath. Then a solution involving only fewer satellites than are in view will be solved for. Baseline testing was done in clear sky in an open field at Auburn University. Multipath testing was also done with antennas on a test vehicle in downtown Atlanta, an area known to be an urban canyon with high instances of multipath, as well as around downtown Auburn, where multipath is possible, but not as detrimental as in downtown Atlanta. The algorithm’s ability to navigate using only three satellites Finally, the proposed technique will be compared to other multipath algorithms developed at Auburn University, which include angle-of-arrival (AOA) and carrier-phase residual techniques.

@unpublished{salmon_guidance_2013,
	type = {thesis},
	title = {Guidance of an {Off}-{Road} {Tractor}-{Trailer} {System} {Using} {Model} {Predictive} {Control}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/3893},
	abstract = {This thesis presents an effort to improve the path following reliability of a tractor-trailer system by using a non-linear Model Predictive Control (MPC) approach. The proposed method allows an autonomous mobile robot to make informed control decisions based on anticipating changes in the path conditions, rather than reacting to them, which could potentially reduce path following error on turns.
Using a non-linear tractor-trailer model, the controller takes the tractor’s measured position and heading, as well as information about the path geometry in front of it, and it determines the optimal steer angle. Then, in the case of an Ackerman-steered vehicle, a secondary algorithm takes the desired steer angle and calculates the amount of voltage to apply to the steering wheel motor to achieve the steer angle. In comparison, a differential- steered, or skid-steered vehicle takes the set point (given as a turn rate in radians per second) and computes the voltages to the traction motors internally.
In the MATLAB simulation study, the controller algorithm is capable of guiding a 2- 1/2 meter long trailer around a 5-meter radius turn, when towed by a four wheel drive off-road utility vehicle, with a maximum error of 8.5 centimeters. These results are highly idealized, however. Adding sensor noise and process noise in simulation increases the error, and inherent sensor bias and latency during the live run increases the error substantially.
From the experimental results, it is concluded that non-linear MPC has the potential to improve the reliability of the path following of a robot and trailer system. In order to fully reap the benefits of non-linear MPC however, the model has to be accurate, and the computer has to be fast enough to compute predictions from the model in real-time.},
	language = {en},
	urldate = {2024-06-25},
	author = {Salmon, James},
	month = nov,
	year = {2013},
	note = {Accepted: 2013-11-08T20:16:56Z},
}

This thesis presents an effort to improve the path following reliability of a tractor-trailer system by using a non-linear Model Predictive Control (MPC) approach. The proposed method allows an autonomous mobile robot to make informed control decisions based on anticipating changes in the path conditions, rather than reacting to them, which could potentially reduce path following error on turns. Using a non-linear tractor-trailer model, the controller takes the tractor’s measured position and heading, as well as information about the path geometry in front of it, and it determines the optimal steer angle. Then, in the case of an Ackerman-steered vehicle, a secondary algorithm takes the desired steer angle and calculates the amount of voltage to apply to the steering wheel motor to achieve the steer angle. In comparison, a differential- steered, or skid-steered vehicle takes the set point (given as a turn rate in radians per second) and computes the voltages to the traction motors internally. In the MATLAB simulation study, the controller algorithm is capable of guiding a 2- 1/2 meter long trailer around a 5-meter radius turn, when towed by a four wheel drive off-road utility vehicle, with a maximum error of 8.5 centimeters. These results are highly idealized, however. Adding sensor noise and process noise in simulation increases the error, and inherent sensor bias and latency during the live run increases the error substantially. From the experimental results, it is concluded that non-linear MPC has the potential to improve the reliability of the path following of a robot and trailer system. In order to fully reap the benefits of non-linear MPC however, the model has to be accurate, and the computer has to be fast enough to compute predictions from the model in real-time.

@unpublished{broshears_ultra-wideband_2013,
	type = {thesis},
	title = {Ultra-wideband {Radio} {Aided} {Carrier} {Phase} {Ambiguity} {Resolution} in {Real}-{Time} {Kinematic} {GPS} {Relative} {Positioning}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/3704},
	abstract = {In this thesis, ultra-wideband radios (UWBs) are integrated into the real-time kinematic (RTK) algorithm using differential GPS techniques to achieve a highly precise relative positioning vector between GPS antennas. This has potential applications including an autonomous leader-follower scenario or an unmanned aerial refueling scenario. The UWBs give a range measurement between antennas, while the RTK solution gives a three dimensional relative positioning vector. This UWB range measurement can be integrated into the RTK algorithm to add robustness and increase accuracy.
When two GPS receivers are within a close proximity, most of the errors that degrade the GPS signal are correlated between the two receivers and can be mitigated by using differential techniques. This can be done using either a static base station, as is the case for RTK, or using a dynamic base, as is the case for DRTK. These algorithms are explained in detail in this thesis, as well as results showing the improved accuracy.
The difficulty of the RTK algorithm is that it must resolve ambiguities in the carrier phase once the receiver has locked on to a satellite’s signal. The least squares ambiguity adjustment (LAMBDA) method was created to help resolve these ambiguities. When the baseline between GPS antennas is known, this known baseline can be used as a constraint and can be integrated into the LAMBDA method, resulting in a C-LAMBDA method. This thesis uses the UWB range measurements in place of the known baseline in the C-LAMBDA method and results showing its improvement over the standard LAMBDA method are presented.
By looking at the experimental results, some conclusions can be made. As long as the accuracy of the UWB range measurements is within a few centimeters, it is shown that it can be used in the C-LAMBDA method as the baseline constraint in helping to resolve the carrier phase ambiguities.},
	language = {en},
	urldate = {2024-06-25},
	author = {Broshears, Eric},
	month = jul,
	year = {2013},
	note = {Accepted: 2013-07-10T18:20:58Z},
}

In this thesis, ultra-wideband radios (UWBs) are integrated into the real-time kinematic (RTK) algorithm using differential GPS techniques to achieve a highly precise relative positioning vector between GPS antennas. This has potential applications including an autonomous leader-follower scenario or an unmanned aerial refueling scenario. The UWBs give a range measurement between antennas, while the RTK solution gives a three dimensional relative positioning vector. This UWB range measurement can be integrated into the RTK algorithm to add robustness and increase accuracy. When two GPS receivers are within a close proximity, most of the errors that degrade the GPS signal are correlated between the two receivers and can be mitigated by using differential techniques. This can be done using either a static base station, as is the case for RTK, or using a dynamic base, as is the case for DRTK. These algorithms are explained in detail in this thesis, as well as results showing the improved accuracy. The difficulty of the RTK algorithm is that it must resolve ambiguities in the carrier phase once the receiver has locked on to a satellite’s signal. The least squares ambiguity adjustment (LAMBDA) method was created to help resolve these ambiguities. When the baseline between GPS antennas is known, this known baseline can be used as a constraint and can be integrated into the LAMBDA method, resulting in a C-LAMBDA method. This thesis uses the UWB range measurements in place of the known baseline in the C-LAMBDA method and results showing its improvement over the standard LAMBDA method are presented. By looking at the experimental results, some conclusions can be made. As long as the accuracy of the UWB range measurements is within a few centimeters, it is shown that it can be used in the C-LAMBDA method as the baseline constraint in helping to resolve the carrier phase ambiguities.

@unpublished{bitner_detection_2013,
	type = {thesis},
	title = {Detection and {Removal} of {Erroneous} {GPS} {Signals} {Using} {Angle} of {Arrival}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/3888},
	abstract = {In this thesis, an algorithm for detecting multipath and spoofed GPS signals based on signal angle of arrival (AOA) is developed. As the first step in determining the AOA of the signals, a multi-antenna array of GPS antennas is used to determine the attitude of a test vehicle by calculating precise relative positioning vectors (RPVs) between the antennas. The RPVs are calculated with the real-time kinematic (RTK) positioning algorithm, which allows for an RPV error on the order of a centimeter. The precision of the RPVs allows for sub-degree accuracy of the attitude angles.

Abstract A GPS/INS extended Kalman filter is used to propagate the attitude estimate between GPS measurements. The propagated attitude estimate allows for estimation of the RPVs between the antennas without using GPS measurements. To check an incoming set of GPS measurements, an expected AOA with respect to the antennas is computed using the estimated RPVs and the known unit vectors to the GPS satellites. The actual AOAs may be estimated using the incoming GPS measurements and then compared with the expected AOAs. If the difference between the expected and estimated AOA for a signal is not within a specified threshold, the signal may be rejected as a faulty signal. Single-differenced pseudorange measurements and single-differenced carrier phase residuals are explored as alternate metrics for determining faulty signals. 

Abstract Finally, AOA and the alternate metrics are experimentally tested for their abilities to detect multipath signals and are compared with each other. The single-differenced carrier phase residual proved to be the most reliable multipath detection metric when used with calculated RPVs, having a near perfect success rate with the collected data. Using the carrier phase residual metric with attitude-generated RPVs proved to be less effective with a success rate of approximately 50\%. The AOA approach had a similar success rate of about 50\%, with worse results in instances of repeated multipath. The single-differenced pseudorange metric proved unable to reliably detect multipath due to the short antenna baselines and relatively large error on pseudorange measurements. The experimental results are validated by comparing positioning solutions before and after rejecting the signals as well as observing the pseudorange measurements of signals detected as multipath.},
	language = {en},
	urldate = {2024-06-25},
	author = {Bitner, Thomas},
	month = nov,
	year = {2013},
	note = {Accepted: 2013-11-08T16:55:09Z},
}

In this thesis, an algorithm for detecting multipath and spoofed GPS signals based on signal angle of arrival (AOA) is developed. As the first step in determining the AOA of the signals, a multi-antenna array of GPS antennas is used to determine the attitude of a test vehicle by calculating precise relative positioning vectors (RPVs) between the antennas. The RPVs are calculated with the real-time kinematic (RTK) positioning algorithm, which allows for an RPV error on the order of a centimeter. The precision of the RPVs allows for sub-degree accuracy of the attitude angles. Abstract A GPS/INS extended Kalman filter is used to propagate the attitude estimate between GPS measurements. The propagated attitude estimate allows for estimation of the RPVs between the antennas without using GPS measurements. To check an incoming set of GPS measurements, an expected AOA with respect to the antennas is computed using the estimated RPVs and the known unit vectors to the GPS satellites. The actual AOAs may be estimated using the incoming GPS measurements and then compared with the expected AOAs. If the difference between the expected and estimated AOA for a signal is not within a specified threshold, the signal may be rejected as a faulty signal. Single-differenced pseudorange measurements and single-differenced carrier phase residuals are explored as alternate metrics for determining faulty signals. Abstract Finally, AOA and the alternate metrics are experimentally tested for their abilities to detect multipath signals and are compared with each other. The single-differenced carrier phase residual proved to be the most reliable multipath detection metric when used with calculated RPVs, having a near perfect success rate with the collected data. Using the carrier phase residual metric with attitude-generated RPVs proved to be less effective with a success rate of approximately 50%. The AOA approach had a similar success rate of about 50%, with worse results in instances of repeated multipath. The single-differenced pseudorange metric proved unable to reliably detect multipath due to the short antenna baselines and relatively large error on pseudorange measurements. The experimental results are validated by comparing positioning solutions before and after rejecting the signals as well as observing the pseudorange measurements of signals detected as multipath.

@unpublished{wooten_high-dynamic_2013,
	type = {thesis},
	title = {High-{Dynamic} {Range} {Collision} {Detection} using {Piezoelectric} {Polymer} {Films} for {Planar} and {Non}-planar {Applications}},
	copyright = {EMBARGO\_GLOBAL},
	url = {https://etd.auburn.edu//handle/10415/3698},
	abstract = {This thesis develops a large area collision detection system utilizing the piezoelectric ef-
fect of polyvinylidene fluoride film. Complex high speed autonomous articulations associated
with modern large-scale high degree-of-freedom (DOF) robotic arms have a high possibility
of collision when integrated into human cooperative environments for human-aid, task au-
tomation, and biomedical interfacing. The proposed system provides high dynamic range for
sensation and robust adaptability to achieve collision detection on complex surfaces in order
to augment robotic systems with collision perception. The design allows for increased cohabi-
tation of human and high DOF robotic arms in cooperative environments requiring advanced
and robust collision detection systems capable of retrofitting onto deployed and operating
robotic arms in the commercial world. Sensor testing is accomplished using multiple collision
stimuli to mimic real world performance as well as impact force modeling utilizing high speed
cameras. The experimentation results show a wide dynamic sensing range for collision force,
from 5N to 300N and consistent sensor response for planar and non-planar applications.
The thesis will show and support the sensor capability of wide range of collision detection
while maintaining adaptability of sensor design to multiple scenarios. The approach differs
from current work which primarily focuses on small-range low levels of tactician perception,
small area sensor requiring complex construction, and associated electronics and processing
complexity for common approaches. The pseudo-membrane design eliminates the construc-
tion complexity and limited application scope while achieving high and low levels of collision
detection utilizing simple electronics and processing method. The captured experimentation
results highlight the consistency of response for multiple applications, standard deviation
of results less than 1GPa, and the large range of collision detection capability from 5N to
300N.},
	language = {en},
	urldate = {2024-06-25},
	author = {Wooten, James Michael},
	month = jul,
	year = {2013},
	note = {Accepted: 2013-07-10T16:17:26Z},
}

This thesis develops a large area collision detection system utilizing the piezoelectric ef- fect of polyvinylidene fluoride film. Complex high speed autonomous articulations associated with modern large-scale high degree-of-freedom (DOF) robotic arms have a high possibility of collision when integrated into human cooperative environments for human-aid, task au- tomation, and biomedical interfacing. The proposed system provides high dynamic range for sensation and robust adaptability to achieve collision detection on complex surfaces in order to augment robotic systems with collision perception. The design allows for increased cohabi- tation of human and high DOF robotic arms in cooperative environments requiring advanced and robust collision detection systems capable of retrofitting onto deployed and operating robotic arms in the commercial world. Sensor testing is accomplished using multiple collision stimuli to mimic real world performance as well as impact force modeling utilizing high speed cameras. The experimentation results show a wide dynamic sensing range for collision force, from 5N to 300N and consistent sensor response for planar and non-planar applications. The thesis will show and support the sensor capability of wide range of collision detection while maintaining adaptability of sensor design to multiple scenarios. The approach differs from current work which primarily focuses on small-range low levels of tactician perception, small area sensor requiring complex construction, and associated electronics and processing complexity for common approaches. The pseudo-membrane design eliminates the construc- tion complexity and limited application scope while achieving high and low levels of collision detection utilizing simple electronics and processing method. The captured experimentation results highlight the consistency of response for multiple applications, standard deviation of results less than 1GPa, and the large range of collision detection capability from 5N to 300N.

@inproceedings{wooten_robust_2013,
	title = {Robust large-area piezoelectric polymer-based collision detection sensor},
	url = {https://ieeexplore.ieee.org/abstract/document/6699774},
	doi = {10.1109/IECON.2013.6699774},
	abstract = {Complex high speed autonomous articulations associated with modern large-scale high degree-of-freedom (DOF) robotic arms have a high possibility of collision when integrated into human cooperative environments for human-aid, task automation, and biomedical interfacing. This paper proposes a large area collision detection system utilizing the piezoelectric effect of polyvinylidene fluoride film. The proposed system provides high dynamic range for sensation and robust adaptability to achieve collision detection on complex surfaces in order to augment robotic systems with collision perception. The design allows for increased cohabitation of human and high DOF robotic arms in cooperative environments requiring advanced and robust collision detection systems capable of retrofitting onto deployed and operating robotic arms in the commercial world.},
	urldate = {2024-06-20},
	booktitle = {{IECON} 2013 - 39th {Annual} {Conference} of the {IEEE} {Industrial} {Electronics} {Society}},
	author = {Wooten, J. Michael and Bevly, David M. and Hung, John Y.},
	month = nov,
	year = {2013},
	note = {ISSN: 1553-572X},
	keywords = {Force, Robot sensing systems, Strain, Stress, Substrates},
	pages = {3994--3999},
}

Complex high speed autonomous articulations associated with modern large-scale high degree-of-freedom (DOF) robotic arms have a high possibility of collision when integrated into human cooperative environments for human-aid, task automation, and biomedical interfacing. This paper proposes a large area collision detection system utilizing the piezoelectric effect of polyvinylidene fluoride film. The proposed system provides high dynamic range for sensation and robust adaptability to achieve collision detection on complex surfaces in order to augment robotic systems with collision perception. The design allows for increased cohabitation of human and high DOF robotic arms in cooperative environments requiring advanced and robust collision detection systems capable of retrofitting onto deployed and operating robotic arms in the commercial world.

@inproceedings{cofield_-line_2013,
	title = {An {On}-{Line} {Visual} {Driver} {Aid} for {Safe} and {Precise} {Convoy} {Following} in {Visibility}-{Impaired} {Conditions}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=11148},
	abstract = {The use of vehicle convoys is common in transportation, where safety and path precision are frequently desired. Extremely close spacing can be used to reduce fuel costs, but introduces a collision risk. In other cases, when traveling over a path that has unstable or dangerous areas nearby, a following vehicle attempts to stay within the track of a vehicle ahead. When visibility is impaired, the ability of any convoy driver to adhere to a path of known safety, and the ability to avoid colliding with the leader is significantly reduced. Real-time path fidelity information is sought which will enable the following driver to intuitively and safely maintain a high-fidelity execution of the desired path during situations in which the leader is either not directly visible or close enough that the risk of collision is imminent. A driver aid utilizing GNSS positioning is presented which will augment or replace visual cues in scenarios where line-of-sight is unreliable or unavailable, regardless of the ground-based deployment platform. Dynamic-base Real-Time Kinematic (DRTK) GPS is used to find a relative position from the leader to the follower, while the Time Differenced Carrier Phase (TDCP) measurement is used to compute the change in position of both vehicles. Both of these measurements are recorded over time to yield the path taken by the leader relative to the follower with very high accuracy. The results are refined to preserve only information immediately relevant to the following task and presented on a Graphical User Interface (GUI). Relevant information may comprise distance to the nearest path point as measured along the vehicle's lateral axis (“path deviation”), curvilinear path spacing to adjacent lead vehicle, present velocity, and any associated risk factor. The primary risk factor examined is rear-end collision, which becomes increasingly probable during low-visibility conditions. For a given platform, vehicle dynamic characteristics will greatly influence the desired spacing and ground speed, as well as the ability to minimize lateral deviation from the path of a leader with dissimilar dynamics. Accordingly, a set of driver-input scalar parameters necessary for platform and scenario independence is determined by examining driver performance using the GUI with several simulated vehicle models and environments, the results of which are presented herein. A first-person driver seat view is replicated on computer screens using user input from a steering wheel and pedals. From these trials, features to accept corresponding driver inputs are incorporated into the GUI such that modification is possible while driving without presenting a distraction from the driving task. This necessitates an interface view which is clean and devoid of non-essential information. Once this has been accomplished, safety warnings are refined without risk of damaging equipment. Ranges of acceptable braking are input by the driver for various safety hazard levels. Upon crossing one of these predetermined thresholds given instantaneous velocity or curvilinear following distance, a negative longitudinal acceleration violating a corresponding limit would be required to avoid collision with the leader. The appropriate warning is relayed to the driver warning of the risk. Testing is then performed in multiple platforms of varied dynamic characteristics to evaluate fidelity gains with respect to two variables: direct line-of-sight and visible cues. A performance improvement test is first conducted in environments benign to the following task, in which drivers are asked to perform a similar task both with and without the aid of the GUI presented. In this manner, fidelity gains are evaluated when the presence of lane markings and other visually distinct features make path replication much simpler. Another set of tests is then presented with terrain cues removed, similar to a desert driving scene without any objects or markings useful for relative localization. Line-of-sight is maintained throughout this test as well. Scenarios are then constructed which make high-fidelity path replication extremely difficult to impossible without aid; drivers are asked to replicate an intricate path without any line-of-sight or visual markers, using the GUI for navigation. In all test cases, simulated and actual, the metric by which driver performance is scored is based upon drivers' minimization of lateral deviation and ability to keep constant following distance goals. In instances where erratic paths result in rapidly changing ground speeds, a constant spacing may not be practical. In these instances, it is expected that a following driver should maintain a velocity equal to the leader's velocity at the same position. All of these qualifiers are analyzed in detail during post-processing. In this way the GUI will be shown to be significantly beneficial to aiding convoy drivers in high precision following.},
	language = {en},
	urldate = {2024-06-20},
	author = {Cofield, R. and Martin, S. and Bevly, D.},
	month = sep,
	year = {2013},
	pages = {704--710},
}

The use of vehicle convoys is common in transportation, where safety and path precision are frequently desired. Extremely close spacing can be used to reduce fuel costs, but introduces a collision risk. In other cases, when traveling over a path that has unstable or dangerous areas nearby, a following vehicle attempts to stay within the track of a vehicle ahead. When visibility is impaired, the ability of any convoy driver to adhere to a path of known safety, and the ability to avoid colliding with the leader is significantly reduced. Real-time path fidelity information is sought which will enable the following driver to intuitively and safely maintain a high-fidelity execution of the desired path during situations in which the leader is either not directly visible or close enough that the risk of collision is imminent. A driver aid utilizing GNSS positioning is presented which will augment or replace visual cues in scenarios where line-of-sight is unreliable or unavailable, regardless of the ground-based deployment platform. Dynamic-base Real-Time Kinematic (DRTK) GPS is used to find a relative position from the leader to the follower, while the Time Differenced Carrier Phase (TDCP) measurement is used to compute the change in position of both vehicles. Both of these measurements are recorded over time to yield the path taken by the leader relative to the follower with very high accuracy. The results are refined to preserve only information immediately relevant to the following task and presented on a Graphical User Interface (GUI). Relevant information may comprise distance to the nearest path point as measured along the vehicle's lateral axis (“path deviation”), curvilinear path spacing to adjacent lead vehicle, present velocity, and any associated risk factor. The primary risk factor examined is rear-end collision, which becomes increasingly probable during low-visibility conditions. For a given platform, vehicle dynamic characteristics will greatly influence the desired spacing and ground speed, as well as the ability to minimize lateral deviation from the path of a leader with dissimilar dynamics. Accordingly, a set of driver-input scalar parameters necessary for platform and scenario independence is determined by examining driver performance using the GUI with several simulated vehicle models and environments, the results of which are presented herein. A first-person driver seat view is replicated on computer screens using user input from a steering wheel and pedals. From these trials, features to accept corresponding driver inputs are incorporated into the GUI such that modification is possible while driving without presenting a distraction from the driving task. This necessitates an interface view which is clean and devoid of non-essential information. Once this has been accomplished, safety warnings are refined without risk of damaging equipment. Ranges of acceptable braking are input by the driver for various safety hazard levels. Upon crossing one of these predetermined thresholds given instantaneous velocity or curvilinear following distance, a negative longitudinal acceleration violating a corresponding limit would be required to avoid collision with the leader. The appropriate warning is relayed to the driver warning of the risk. Testing is then performed in multiple platforms of varied dynamic characteristics to evaluate fidelity gains with respect to two variables: direct line-of-sight and visible cues. A performance improvement test is first conducted in environments benign to the following task, in which drivers are asked to perform a similar task both with and without the aid of the GUI presented. In this manner, fidelity gains are evaluated when the presence of lane markings and other visually distinct features make path replication much simpler. Another set of tests is then presented with terrain cues removed, similar to a desert driving scene without any objects or markings useful for relative localization. Line-of-sight is maintained throughout this test as well. Scenarios are then constructed which make high-fidelity path replication extremely difficult to impossible without aid; drivers are asked to replicate an intricate path without any line-of-sight or visual markers, using the GUI for navigation. In all test cases, simulated and actual, the metric by which driver performance is scored is based upon drivers' minimization of lateral deviation and ability to keep constant following distance goals. In instances where erratic paths result in rapidly changing ground speeds, a constant spacing may not be practical. In these instances, it is expected that a following driver should maintain a velocity equal to the leader's velocity at the same position. All of these qualifiers are analyzed in detail during post-processing. In this way the GUI will be shown to be significantly beneficial to aiding convoy drivers in high precision following.

@inproceedings{wang_robust_2013,
	address = {Palo Alto, California, USA},
	title = {Robust {Observer} {Design} for {Lipschitz} {Nonlinear} {Systems} {With} {Parametric} {Uncertainty}},
	isbn = {978-0-7918-5614-7},
	url = {https://asmedigitalcollection.asme.org/DSCC/proceedings/DSCC2013/56147/Palo%20Alto,%20California,%20USA/228856},
	doi = {10.1115/DSCC2013-4104},
	abstract = {This paper discusses optimal and robust observer design for the Lipschitz nonlinear systems. The stability analysis for the Lure problem is first reviewed. Then, a two-DOF nonlinear observer is proposed so that the observer error dynamic model can be transformed to an equivalent Lure system. In this framework, the difference of the nonlinear parts in the vector fields of the original system and observer is modeled as a nonlinear memoryless block that is covered by a multivariable sector condition or an equivalent semi-algebraic set defined by a quadratic polynomial inequality. Then, a sufficient condition for asymptotic stability of the observer error dynamics is formulated in terms of the feasibility of polynomial matrix inequalities (PMIs), which can be solved by Lasserre’s moment relaxation. Furthermore, various quadratic performance criteria, such as H2 and H∞, can be easily incorporated in this framework. Finally, a parameter adaptation algorithm is introduced to cope with the parameter uncertainty.},
	urldate = {2024-06-20},
	booktitle = {Volume 3: {Nonlinear} {Estimation} and {Control}; {Optimization} and {Optimal} {Control}; {Piezoelectric} {Actuation} and {Nanoscale} {Control}; {Robotics} and {Manipulators}; {Sensing}; {System} {Identification} ({Estimation} for {Automotive} {Applications}, {Modeling}, {Therapeutic} {Control} in {Bio}-{Systems}); {Variable} {Structure}/{Sliding}-{Mode} {Control}; {Vehicles} and {Human} {Robotics}; {Vehicle} {Dynamics} and {Control}; {Vehicle} {Path} {Planning} and {Collision} {Avoidance}; {Vibrational} and {Mechanical} {Systems}; {Wind} {Energy} {Systems} and {Control}},
	publisher = {American Society of Mechanical Engineers},
	author = {Wang, Yan and Bevly, David M.},
	month = oct,
	year = {2013},
	pages = {V003T35A006},
}

This paper discusses optimal and robust observer design for the Lipschitz nonlinear systems. The stability analysis for the Lure problem is first reviewed. Then, a two-DOF nonlinear observer is proposed so that the observer error dynamic model can be transformed to an equivalent Lure system. In this framework, the difference of the nonlinear parts in the vector fields of the original system and observer is modeled as a nonlinear memoryless block that is covered by a multivariable sector condition or an equivalent semi-algebraic set defined by a quadratic polynomial inequality. Then, a sufficient condition for asymptotic stability of the observer error dynamics is formulated in terms of the feasibility of polynomial matrix inequalities (PMIs), which can be solved by Lasserre’s moment relaxation. Furthermore, various quadratic performance criteria, such as H2 and H∞, can be easily incorporated in this framework. Finally, a parameter adaptation algorithm is introduced to cope with the parameter uncertainty.

@inproceedings{salmon_guidance_2013,
	address = {Palo Alto, California, USA},
	title = {Guidance of a {Robotic} {Off}-{Road} {Tractor}-{Trailer} {System} {Using} {Model} {Predictive} {Control}},
	isbn = {978-0-7918-5614-7},
	url = {https://asmedigitalcollection.asme.org/DSCC/proceedings/DSCC2013/56147/Palo%20Alto,%20California,%20USA/228870},
	doi = {10.1115/DSCC2013-3858},
	abstract = {This paper presents a nonlinear Model Predictive Control approach to controlling a tractor-trailer system. Using a nonlinear tractor-trailer model, the controller determines the optimal steer angle, based on the trailer’s measured position and heading, as well as information about the path geometry in front of it. Then, the computer determines the amount of voltage to apply to the steering wheel motor to achieve the necessary steer angle. In the simulation study, the controller algorithm is capable of guiding a 2-1/2 meter long trailer around a 5-meter radius turn, towed by a four wheel drive off-road utility vehicle, with a maximum error of 8.5 centimeters.},
	urldate = {2024-06-20},
	booktitle = {Volume 3: {Nonlinear} {Estimation} and {Control}; {Optimization} and {Optimal} {Control}; {Piezoelectric} {Actuation} and {Nanoscale} {Control}; {Robotics} and {Manipulators}; {Sensing}; {System} {Identification} ({Estimation} for {Automotive} {Applications}, {Modeling}, {Therapeutic} {Control} in {Bio}-{Systems}); {Variable} {Structure}/{Sliding}-{Mode} {Control}; {Vehicles} and {Human} {Robotics}; {Vehicle} {Dynamics} and {Control}; {Vehicle} {Path} {Planning} and {Collision} {Avoidance}; {Vibrational} and {Mechanical} {Systems}; {Wind} {Energy} {Systems} and {Control}},
	publisher = {American Society of Mechanical Engineers},
	author = {Salmon, James T. and Bevly, David M. and Hung, John Y.},
	month = oct,
	year = {2013},
	pages = {V003T47A001},
}

This paper presents a nonlinear Model Predictive Control approach to controlling a tractor-trailer system. Using a nonlinear tractor-trailer model, the controller determines the optimal steer angle, based on the trailer’s measured position and heading, as well as information about the path geometry in front of it. Then, the computer determines the amount of voltage to apply to the steering wheel motor to achieve the necessary steer angle. In the simulation study, the controller algorithm is capable of guiding a 2-1/2 meter long trailer around a 5-meter radius turn, towed by a four wheel drive off-road utility vehicle, with a maximum error of 8.5 centimeters.

@inproceedings{broshears_ultra-wideband_2013,
	title = {Ultra-{Wideband} {Aided} {Carrier} {Phase} {Ambiguity} {Resolution} in {Real}-{Time} {Kinematic} {GPS} {Relative} {Positioning}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=11323},
	abstract = {This research paper presents results that show incorporating the accurate range measurements from ultra-wideband radios into the baseline-constrained LAMBDA method of the RTK algorithms helps improve the time-to-fix of the carrier phase integer ambiguities. The higher frequency and accuracy of the UWBs also help the robustness of the position solution by detecting faulty signals and cycle slips. The results show quicker time-to-fix with the UWB measurements than the standard LAMBDA method would get alone. This research can be applied to any sort of dynamic situation in which two GPS receivers and two UWBs are coupled parallel to each other and are within a relatively close proximity. Ever since GPS was first implemented, it has been used to aid navigation. Accuracy of the position solutions limit GPS usage to certain navigation applications. Typical accuracy of position solutions for raw GPS signals is around 5-10 meters. Atmospheric errors are among the biggest contributors to the degradation of the GPS signal; but for relatively close distances, these atmospheric errors are highly correlated and can be differenced out between two different GPS receivers. Mitigating these common errors between receivers can bring the accuracy of the relative positioning between receivers down to less than 1 meter. However, some additional differential corrections can be made if the relative carrier phase integer ambiguities between the receivers are found. Once these integer ambiguities are resolved, the position solution accuracy can get down to less than 3 centimeters. The objective of the research in this work is to integrate the range measurements from ultra-wideband (UWB) radios into the differential GPS positioning algorithms to help resolve the carrier phase ambiguities quicker and more reliably. Relative positioning is especially important in navigation, so the ability to gain extremely accurate global positioning measurements is critical for certain applications; examples of such applications could include: an autonomous helicopter landing on an aircraft carrier, an unmanned aerial vehicle airborne refueling, or a leader-follower autonomous driving scenario. Resolving these ambiguities is no trivial task, especially if using lower cost single-frequency GPS receivers. Luckily, the researchers at the Delft University of Technology, headed by Peter Teunissen, have created what is now known as the Least-Squares Ambiguity Decorrelation Adjustment (LAMBDA) method. This algorithm decorrelates the covariance of the errors to the receivers common satellites and creates a more efficient search space to look for the integer ambiguities. The LAMBDA method has been around for several decades, and new improvements are continually being researched to add to this method. One of the additions to this method is a baseline-constrained LAMBDA, or C-LAMBDA, which can take a priori knowledge of the baseline between GPS receivers and integrate it into the LAMBDA method to reduce the search space for the integer ambiguities. Applications for the C-LAMBDA method include scenarios in which the GPS antennas are mounted onto a platform on a vehicle. If three antennas are mounted in a triangle at known distances, then the attitude of the vehicle can be determined. This baseline constraint can resolve the ambiguities quicker than the typical LAMBDA method and also adds an element of robustness to the method to protect it against multi-path and other errors that affect the GPS signal that cannot be differenced out between receivers. Ultra-wideband radios are a relatively new type of technology that unlike radios, which use sinusoidal frequency transmissions, use a quick impulse sent out over a wide range of frequencies. When two or more UWBs are placed in close proximity, approximately less than 100 meters, they can calculate the time-of-flight between antennas and derive a range measurement that is centimeter-level accurate. With a frequency of up to about 30 Hz, UWBs also have a much higher frequency than most GPS receivers. This technology is being researched to aid small convoys of autonomous aerial and ground vehicles. The objective of this paper is to successfully integrate the range measurements from the UWBs into the C-LAMBDA method, essentially treating the UWB measurements as a baseline constraint. Several implications have been considered when integrating the UWBs into the C-LAMBDA method. Aside from the UWB ranging measurements being used in the C-LAMBDA method to resolve the integer ambiguities, the UWBs could also be used as a validation on the normal LAMBDA method. This would allow for the UWBs to check for cycle slips or GPS measurement fault detection. The wavelength of the L1 GPS signal is about 19 centimeters, so the accuracy required of the range measurements to successfully detect cycle slips will be investigated. If the UWB measurement accuracy is below the length altered by a single cycle slip, then it should be able to be used as a cycle slip detector. Results include a quicker time-to-fix for the carrier phase integer ambiguities. With a single-frequency GPS receiver, this time-to-fix can take up to ten minutes, sometimes longer. Dual-frequency GPS receivers can usually resolve the ambiguities within 30 seconds, depending on the conditions and dynamics of the receivers. The integer ambiguities must be reset every time a satellite is acquired or dropped and also when a cycle slip is detected. Because of this, a shorter time-to-fix can be crucial for a dynamic situation when the ambiguities are frequently being reset. As long as the UWBs provide centimeter-level accuracy, using the UWB ranging measurements should help to improve the time-to-fix of the ambiguities consistently.},
	language = {en},
	urldate = {2024-06-20},
	author = {Broshears, E. and Martin, S. and Bevly, D.},
	month = sep,
	year = {2013},
	pages = {1277--1284},
}

This research paper presents results that show incorporating the accurate range measurements from ultra-wideband radios into the baseline-constrained LAMBDA method of the RTK algorithms helps improve the time-to-fix of the carrier phase integer ambiguities. The higher frequency and accuracy of the UWBs also help the robustness of the position solution by detecting faulty signals and cycle slips. The results show quicker time-to-fix with the UWB measurements than the standard LAMBDA method would get alone. This research can be applied to any sort of dynamic situation in which two GPS receivers and two UWBs are coupled parallel to each other and are within a relatively close proximity. Ever since GPS was first implemented, it has been used to aid navigation. Accuracy of the position solutions limit GPS usage to certain navigation applications. Typical accuracy of position solutions for raw GPS signals is around 5-10 meters. Atmospheric errors are among the biggest contributors to the degradation of the GPS signal; but for relatively close distances, these atmospheric errors are highly correlated and can be differenced out between two different GPS receivers. Mitigating these common errors between receivers can bring the accuracy of the relative positioning between receivers down to less than 1 meter. However, some additional differential corrections can be made if the relative carrier phase integer ambiguities between the receivers are found. Once these integer ambiguities are resolved, the position solution accuracy can get down to less than 3 centimeters. The objective of the research in this work is to integrate the range measurements from ultra-wideband (UWB) radios into the differential GPS positioning algorithms to help resolve the carrier phase ambiguities quicker and more reliably. Relative positioning is especially important in navigation, so the ability to gain extremely accurate global positioning measurements is critical for certain applications; examples of such applications could include: an autonomous helicopter landing on an aircraft carrier, an unmanned aerial vehicle airborne refueling, or a leader-follower autonomous driving scenario. Resolving these ambiguities is no trivial task, especially if using lower cost single-frequency GPS receivers. Luckily, the researchers at the Delft University of Technology, headed by Peter Teunissen, have created what is now known as the Least-Squares Ambiguity Decorrelation Adjustment (LAMBDA) method. This algorithm decorrelates the covariance of the errors to the receivers common satellites and creates a more efficient search space to look for the integer ambiguities. The LAMBDA method has been around for several decades, and new improvements are continually being researched to add to this method. One of the additions to this method is a baseline-constrained LAMBDA, or C-LAMBDA, which can take a priori knowledge of the baseline between GPS receivers and integrate it into the LAMBDA method to reduce the search space for the integer ambiguities. Applications for the C-LAMBDA method include scenarios in which the GPS antennas are mounted onto a platform on a vehicle. If three antennas are mounted in a triangle at known distances, then the attitude of the vehicle can be determined. This baseline constraint can resolve the ambiguities quicker than the typical LAMBDA method and also adds an element of robustness to the method to protect it against multi-path and other errors that affect the GPS signal that cannot be differenced out between receivers. Ultra-wideband radios are a relatively new type of technology that unlike radios, which use sinusoidal frequency transmissions, use a quick impulse sent out over a wide range of frequencies. When two or more UWBs are placed in close proximity, approximately less than 100 meters, they can calculate the time-of-flight between antennas and derive a range measurement that is centimeter-level accurate. With a frequency of up to about 30 Hz, UWBs also have a much higher frequency than most GPS receivers. This technology is being researched to aid small convoys of autonomous aerial and ground vehicles. The objective of this paper is to successfully integrate the range measurements from the UWBs into the C-LAMBDA method, essentially treating the UWB measurements as a baseline constraint. Several implications have been considered when integrating the UWBs into the C-LAMBDA method. Aside from the UWB ranging measurements being used in the C-LAMBDA method to resolve the integer ambiguities, the UWBs could also be used as a validation on the normal LAMBDA method. This would allow for the UWBs to check for cycle slips or GPS measurement fault detection. The wavelength of the L1 GPS signal is about 19 centimeters, so the accuracy required of the range measurements to successfully detect cycle slips will be investigated. If the UWB measurement accuracy is below the length altered by a single cycle slip, then it should be able to be used as a cycle slip detector. Results include a quicker time-to-fix for the carrier phase integer ambiguities. With a single-frequency GPS receiver, this time-to-fix can take up to ten minutes, sometimes longer. Dual-frequency GPS receivers can usually resolve the ambiguities within 30 seconds, depending on the conditions and dynamics of the receivers. The integer ambiguities must be reset every time a satellite is acquired or dropped and also when a cycle slip is detected. Because of this, a shorter time-to-fix can be crucial for a dynamic situation when the ambiguities are frequently being reset. As long as the UWBs provide centimeter-level accuracy, using the UWB ranging measurements should help to improve the time-to-fix of the ambiguities consistently.

@inproceedings{britt_sensor_2013,
	title = {Sensor {Auto}-{Calibration} on {Dynamic} {Platforms} in {3D}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=11133},
	abstract = {Sensor misalignment can be simply annoying causing fuzzy point clouds or catastrophic when obstacle avoidance sensors are mal-aligned. However, despite the necessity of calibration, the process can often be tedious and time consuming, often requiring external targets or apriori knowledge of the environment. I will demonstrate an auto-calibration scheme that will find the translation and rotation in thee dimensions between any two sensors capable of determining their respective change in position and attitude. This work is an extension of a similar method that has since been confined to only two dimensions. The major benefit to this method over other auto-calibration schemes, is that this method make no inherent assumptions about the environment, needs no calibration target, and is designed to be performed on a vehicle while it is undergoing dynamics. This is especially beneficial to applications where a sensor might be jarred during transit due to the environment, vehicle damage, or when sensors are often repositioned on vehicles. The algorithm in question operates by assuming that there are two sensors where each is capable of determining a local change in pose (position and attitude). The principle being that if the two sensors are perfectly calibrated, they should both experience the same change in pose. A Kalman filter is used to obtain the true translation and rotation between the sensors by attempting to align these changes in pose measurements so that both sensors are sensing the same change in pose. This also implies that should the sensors become misaligned during a mission, they could be re-aligned on the fly. In addition to the calibration method itself, I will analyze the observability of the method. In general the circumstances where the filter is unobservable is when the vehicle can undergo holonomic motion, only makes a single perfect circle, or one of the measurement axes goes unexcited. Typically these are not seen in practice. The algorithm has been validated in simulation and various levels of sensor error have been introduced to exam the robustness of the algorithm. The algorithm will also be tested using real-world data supplied by MIT’s grand challenge team, where the algorithm will attempt to align the Velodyne lidar with the onboard IMU. The change in pose of the lidar will be obtained through the ICP (iterative closest point) algorithm. The results of this algorithm dynamic calibration will be compared to the more controlled environment used in the supplied dataset.},
	language = {en},
	urldate = {2024-06-20},
	author = {Britt, J. and Bevly, D.},
	month = sep,
	year = {2013},
	pages = {2195--2203},
}

Sensor misalignment can be simply annoying causing fuzzy point clouds or catastrophic when obstacle avoidance sensors are mal-aligned. However, despite the necessity of calibration, the process can often be tedious and time consuming, often requiring external targets or apriori knowledge of the environment. I will demonstrate an auto-calibration scheme that will find the translation and rotation in thee dimensions between any two sensors capable of determining their respective change in position and attitude. This work is an extension of a similar method that has since been confined to only two dimensions. The major benefit to this method over other auto-calibration schemes, is that this method make no inherent assumptions about the environment, needs no calibration target, and is designed to be performed on a vehicle while it is undergoing dynamics. This is especially beneficial to applications where a sensor might be jarred during transit due to the environment, vehicle damage, or when sensors are often repositioned on vehicles. The algorithm in question operates by assuming that there are two sensors where each is capable of determining a local change in pose (position and attitude). The principle being that if the two sensors are perfectly calibrated, they should both experience the same change in pose. A Kalman filter is used to obtain the true translation and rotation between the sensors by attempting to align these changes in pose measurements so that both sensors are sensing the same change in pose. This also implies that should the sensors become misaligned during a mission, they could be re-aligned on the fly. In addition to the calibration method itself, I will analyze the observability of the method. In general the circumstances where the filter is unobservable is when the vehicle can undergo holonomic motion, only makes a single perfect circle, or one of the measurement axes goes unexcited. Typically these are not seen in practice. The algorithm has been validated in simulation and various levels of sensor error have been introduced to exam the robustness of the algorithm. The algorithm will also be tested using real-world data supplied by MIT’s grand challenge team, where the algorithm will attempt to align the Velodyne lidar with the onboard IMU. The change in pose of the lidar will be obtained through the ICP (iterative closest point) algorithm. The results of this algorithm dynamic calibration will be compared to the more controlled environment used in the supplied dataset.

@article{lashley_performance_2013,
	title = {Performance {Comparison} of {Deep} {Integration} and {Tight} {Coupling}: {Performance} {Comparison} of {DI} and {Tight} {Coupling}},
	volume = {60},
	copyright = {http://doi.wiley.com/10.1002/tdm\_license\_1.1},
	issn = {00281522},
	shorttitle = {Performance {Comparison} of {Deep} {Integration} and {Tight} {Coupling}},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/navi.43},
	doi = {10.1002/navi.43},
	language = {en},
	number = {3},
	urldate = {2024-06-20},
	journal = {Navigation},
	author = {Lashley, Matthew and Bevly, David M.},
	month = sep,
	year = {2013},
	pages = {159--178},
}

@unpublished{singh_nonlinear_2012,
	type = {thesis},
	title = {Nonlinear {Control} of a {Robot}-{Trailer} {System} {Using} a {Hybrid} {Backstepping}-linearizing {Approach}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/3191},
	abstract = {In this work, the author develops a nonlinear controller to stabilize an autonomous wheeled robot and trailer system. A dynamic model based on robot-trailer kinematics that has previously proven sufficient for state feedback control is chosen for the ease of design. An iterative approach similar to backstepping is utilized to obtain the control input. In a manner reminiscent of feedback linearization, nonlinearities are cancelled at each step to obtain an equivalent linear system. This method is significantly different from integrator backstepping method as no signal differentiation is required. However, it is also different from the feedback linearization method as it does not require any coordinate transformation. This hybrid method is essentially a selective amalgamation of the two methods. In contrast to known state-of-the-art approaches, the proposed method stabilizes the system in both the forward and reverse motion directions, without modeling modifications. Simulation results suggest that the Hybrid Backstepping Controller(HBC)is sufficient for regulating the trailer to the desired path from any initial condition. Experimental results confirm that the Hybrid Backstepping Controller(HBC) can control the robot-trailer system and can regulate the trailer over a typical geophysical surveying path.},
	language = {en},
	urldate = {2024-06-25},
	author = {Singh, Aditya},
	month = jul,
	year = {2012},
	note = {Accepted: 2012-07-02T19:20:00Z},
}

In this work, the author develops a nonlinear controller to stabilize an autonomous wheeled robot and trailer system. A dynamic model based on robot-trailer kinematics that has previously proven sufficient for state feedback control is chosen for the ease of design. An iterative approach similar to backstepping is utilized to obtain the control input. In a manner reminiscent of feedback linearization, nonlinearities are cancelled at each step to obtain an equivalent linear system. This method is significantly different from integrator backstepping method as no signal differentiation is required. However, it is also different from the feedback linearization method as it does not require any coordinate transformation. This hybrid method is essentially a selective amalgamation of the two methods. In contrast to known state-of-the-art approaches, the proposed method stabilizes the system in both the forward and reverse motion directions, without modeling modifications. Simulation results suggest that the Hybrid Backstepping Controller(HBC)is sufficient for regulating the trailer to the desired path from any initial condition. Experimental results confirm that the Hybrid Backstepping Controller(HBC) can control the robot-trailer system and can regulate the trailer over a typical geophysical surveying path.

@unpublished{payne_non-collocated_2012,
	type = {thesis},
	title = {Non-collocated {Control} of an {Autonomous} {Robot}-{Trailer} {System} {Using} {State} {Estimation}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/3001},
	abstract = {In this work, the author develops an observer and non-collocated controller for a robot-trailer system in which only the position of the trailer is measured.  A linearized state-space model of the system is derived using kinematic equations that have previously proven sufficient for state feedback control.  Optimal observer gains are calculated using the known measurement noise variance.  Simulation results suggest that the non-collocated position measurements are sufficient to accurately estimate the full system states while successfully regulating the trailer to the desired path.  Experimental results show that the estimator is capable of tracking the system states and that the robot and trailer system can be made to follow a typical geophysical surveying path.},
	language = {en},
	urldate = {2024-06-25},
	author = {Payne, Michael},
	month = apr,
	year = {2012},
	note = {Accepted: 2012-04-09T20:16:23Z},
}

In this work, the author develops an observer and non-collocated controller for a robot-trailer system in which only the position of the trailer is measured. A linearized state-space model of the system is derived using kinematic equations that have previously proven sufficient for state feedback control. Optimal observer gains are calculated using the known measurement noise variance. Simulation results suggest that the non-collocated position measurements are sufficient to accurately estimate the full system states while successfully regulating the trailer to the desired path. Experimental results show that the estimator is capable of tracking the system states and that the robot and trailer system can be made to follow a typical geophysical surveying path.

@unpublished{hill_tire_2012,
	type = {thesis},
	title = {Tire {Force} {Estimation} in {Off}-{Road} {Vehicles} {Using} {Suspension} {Strain} and {Deflection} {Measurements}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/2966},
	abstract = {This thesis develops and analyzes the improvement of tire force estimation and analysis using strain gauge sensors and displacement sensors mounted on the suspension of an all-terrain vehicle. Vehicle dynamic models are developed and validated against simulation data acquired from commercially available CarSIM vehicle simulation software. Improved measurements of the vehicle provide more accurate model parameters used in simulation of the test platform. These improved models are then compared against real data collected from the Prowler All-Terrain Vehicle, a fully instrumented ATV. Suspension force measurement techniques, including strain gauges mounted to the a-arm linkages and deflection potentiometers mounted to the coil-spring assembly were developed and installed onto the testbed. A method for analyzing these force measurements and a methodology to decouple the forces at the tire contact patch into vertical, lateral, and longitudinal components is developed. Results show that this measurement technique is a viable and relatively low-cost method to augment dynamic tire force knowledge in unmanned vehicle systems. Finally, a discussion on the benefits and drawbacks of using this type of sensing method is presented, as well as potential applications of this work.},
	language = {en},
	urldate = {2024-06-25},
	author = {Hill, Ryan},
	month = jan,
	year = {2012},
	note = {Accepted: 2012-01-24T21:33:26Z},
}

This thesis develops and analyzes the improvement of tire force estimation and analysis using strain gauge sensors and displacement sensors mounted on the suspension of an all-terrain vehicle. Vehicle dynamic models are developed and validated against simulation data acquired from commercially available CarSIM vehicle simulation software. Improved measurements of the vehicle provide more accurate model parameters used in simulation of the test platform. These improved models are then compared against real data collected from the Prowler All-Terrain Vehicle, a fully instrumented ATV. Suspension force measurement techniques, including strain gauges mounted to the a-arm linkages and deflection potentiometers mounted to the coil-spring assembly were developed and installed onto the testbed. A method for analyzing these force measurements and a methodology to decouple the forces at the tire contact patch into vertical, lateral, and longitudinal components is developed. Results show that this measurement technique is a viable and relatively low-cost method to augment dynamic tire force knowledge in unmanned vehicle systems. Finally, a discussion on the benefits and drawbacks of using this type of sensing method is presented, as well as potential applications of this work.

@unpublished{brown_roll_2012,
	type = {thesis},
	title = {Roll \& {Bank} {Estimation} {Using} {GPS}/{INS} and {Suspension} {Deflections}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/3263},
	abstract = {This thesis presents three methods that provide and estimate of road bank by decoupling the vehicle roll due to dynamics and roll due road bank. Suspension deflection measurements were used to provide a measurement of the relative roll between the vehicle body frame and the axle frame, or between the sprung mass and the unsprung mass respectively. A method of scaling the suspension deflection measurements to vertical wheel motion was explored. A deflection scaling parameter was found by both a dynamics based method and a suspension geometry based method. The parameter was determined to effectively scale the suspension deflection measurements with minimum error variances over varying vehicle speeds. The relative roll measurement was then incorporated into three different estimation architectures.

A vehicle model based Kalman filter (KF) observer and two kinematic navigation model based extended Kalman filters (EKF) were developed. The first EKF used a cascaded approach to incorporate the relative roll measurement. The EKF second, a coupled approach, augmented the state vector with a state for the road bank. The road bank was modeled as a time varying disturbance and a measurement update for the relative roll measurement was developed. 

All the estimators were used to decouple the vehicle roll due to dynamics and the roll due to bank. Each algorithm was tested in simulation with data from CarSim 6, a vehicle dynamic modeling software package. The estimators were then tested on the Prowler ATV experimental platform at the National Center for Asphalt Technology (NCAT). The KF vehicle model based estimator correctly estimated the road bank under low dynamics in simulation but was susceptible to vehicle model uncertainties and nonlinearities. Both the cascaded and coupled approach performed well for both simulation and experimental data. The EKFs correctly estimated the road crown and banked turns of the NCAT Oval track. The coupled EKF displayed the added benefit of filtering the noise on the bank estimate. 

Between the three estimation approaches the coupled kinematic based EKF approach was determined to be the best method. The vehicle model based approach proved to be very sensitive to the vehicle model. Small deviations in the model led to large bank errors and poor performance under high dynamics. Both of the kinematic based approaches performed well across all ranges of dynamics and road bank disturbances. However, the coupled approach filtered the noise on the bank estimate which was determined to be advantageous.},
	language = {en},
	urldate = {2024-06-25},
	author = {Brown, Lowell},
	month = jul,
	year = {2012},
	note = {Accepted: 2012-07-25T20:29:21Z},
}

This thesis presents three methods that provide and estimate of road bank by decoupling the vehicle roll due to dynamics and roll due road bank. Suspension deflection measurements were used to provide a measurement of the relative roll between the vehicle body frame and the axle frame, or between the sprung mass and the unsprung mass respectively. A method of scaling the suspension deflection measurements to vertical wheel motion was explored. A deflection scaling parameter was found by both a dynamics based method and a suspension geometry based method. The parameter was determined to effectively scale the suspension deflection measurements with minimum error variances over varying vehicle speeds. The relative roll measurement was then incorporated into three different estimation architectures. A vehicle model based Kalman filter (KF) observer and two kinematic navigation model based extended Kalman filters (EKF) were developed. The first EKF used a cascaded approach to incorporate the relative roll measurement. The EKF second, a coupled approach, augmented the state vector with a state for the road bank. The road bank was modeled as a time varying disturbance and a measurement update for the relative roll measurement was developed. All the estimators were used to decouple the vehicle roll due to dynamics and the roll due to bank. Each algorithm was tested in simulation with data from CarSim 6, a vehicle dynamic modeling software package. The estimators were then tested on the Prowler ATV experimental platform at the National Center for Asphalt Technology (NCAT). The KF vehicle model based estimator correctly estimated the road bank under low dynamics in simulation but was susceptible to vehicle model uncertainties and nonlinearities. Both the cascaded and coupled approach performed well for both simulation and experimental data. The EKFs correctly estimated the road crown and banked turns of the NCAT Oval track. The coupled EKF displayed the added benefit of filtering the noise on the bank estimate. Between the three estimation approaches the coupled kinematic based EKF approach was determined to be the best method. The vehicle model based approach proved to be very sensitive to the vehicle model. Small deviations in the model led to large bank errors and poor performance under high dynamics. Both of the kinematic based approaches performed well across all ranges of dynamics and road bank disturbances. However, the coupled approach filtered the noise on the bank estimate which was determined to be advantageous.

@unpublished{woodall_low-bandwidth_2012,
	type = {thesis},
	title = {Low-{Bandwidth} {Three} {Dimensional} {Mapping} and {Latency} {Reducing} {Model} {Prediction} to {Improve} {Teleoperation} of {Robotic} {Vehicles}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/3264},
	abstract = {This thesis uses novel three dimensional sensors like the Microsoft Kinect [1] and the Asus Xtion Pro Live [2] to generate three dimensional environments and use the recon- structed environment with a predictive model in order to assist the teleoperation of mobile vehicles. Ultimately this work would be applicable to any teleoperated vehicle equipped with sensors providing three dimensional data of the environment, such as an automated ATV with a stereo vision system or a Velodyne LiDAR [3] system. The challenges related to utilizing dense three dimensional data in a way that is practical for teleoperation scenar- ios are identified, and solutions are proposed and implemented. To simplify the approach, the problem is split into three smaller tasks: three dimensional mapping, teleoperation and telemetry visualization, and latency reduction techniques. The three dimensional mapping pertains to using the three dimensional sensor data in concert with the mobile vehicle nav- igation solution to generate a three dimensional map of the environment in real-time. The resulting map must be efficiently sent to the teleoperator and visualized in the teleoperation and telemetry visualization section of the thesis. Additionally, latency greatly reduces the teleoperator’s ability to drive the vehicle, so methods for reducing the perceived latency are investigated, including using a vehicle model to simulate the vehicle motion in the absence of timely telemetry updates. It is shown that existing mapping techniques can be used effi- ciently and effective to aid teleoperation, even in low bandwidth environments. Experimental results show that by giving the teleoperator three dimensional information about the envi- ronment, the teleoperator can more successfully navigate tight obstacles and reduce impacts with the environment. Finally, experiments are conducted that show having a prediction of the vehicle motion based on user input can improve teleoperation in high latency situations.},
	language = {en},
	urldate = {2024-06-25},
	author = {Woodall, William},
	month = jul,
	year = {2012},
	note = {Accepted: 2012-07-25T20:56:22Z},
}

This thesis uses novel three dimensional sensors like the Microsoft Kinect [1] and the Asus Xtion Pro Live [2] to generate three dimensional environments and use the recon- structed environment with a predictive model in order to assist the teleoperation of mobile vehicles. Ultimately this work would be applicable to any teleoperated vehicle equipped with sensors providing three dimensional data of the environment, such as an automated ATV with a stereo vision system or a Velodyne LiDAR [3] system. The challenges related to utilizing dense three dimensional data in a way that is practical for teleoperation scenar- ios are identified, and solutions are proposed and implemented. To simplify the approach, the problem is split into three smaller tasks: three dimensional mapping, teleoperation and telemetry visualization, and latency reduction techniques. The three dimensional mapping pertains to using the three dimensional sensor data in concert with the mobile vehicle nav- igation solution to generate a three dimensional map of the environment in real-time. The resulting map must be efficiently sent to the teleoperator and visualized in the teleoperation and telemetry visualization section of the thesis. Additionally, latency greatly reduces the teleoperator’s ability to drive the vehicle, so methods for reducing the perceived latency are investigated, including using a vehicle model to simulate the vehicle motion in the absence of timely telemetry updates. It is shown that existing mapping techniques can be used effi- ciently and effective to aid teleoperation, even in low bandwidth environments. Experimental results show that by giving the teleoperator three dimensional information about the envi- ronment, the teleoperator can more successfully navigate tight obstacles and reduce impacts with the environment. Finally, experiments are conducted that show having a prediction of the vehicle motion based on user input can improve teleoperation in high latency situations.

@unpublished{clark_fault_2012,
	title = {Fault {Detection} and {Exclusion} in {Deeply} {Integrated} {GPS}/{INS} {Navigation}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/3416},
	abstract = {This dissertation presents a novel fault detection and exclusion method in a centralized deeply integrated GPS/INS navigation system.
The method presented is also demonstrated in a centralized vector tracking GPS receiver.
Also, a new multipath error model and a range variance parameter are developed to better deal with the additional challenges faced by vector-based receivers.
These methods and analysis extend the field of robust navigation, particularly with regards to advanced tracking architectures.

GPS was originally designed to operate in clear line of sight view to the supporting satellite constellation.
However, recent advances in receiver hardware and computing power have pushed positioning into more difficult scenarios.
New ways of using radionavigation sensors, such as vector tracking and deeply integrated GPS/INS, have been developed to handle these situations.
However, integrity has been difficult to maintain in these configurations.
Fault detection and exclusion can provide this need by keeping the navigation solution free from erroneous measurements that occur in difficult environments.

This dissertation presents these contributions in four stages.
In the first, a multipath model for vector tracking is developed.
This model is based on a delayed signal's interaction with the direct signal correlation peak rather than the scalar early and late correlator outputs.
To demonstrate both the model and improved performance of vector tracking, simulated results show the vector receiver tracking the signal with 0.015 m less range error.
Experimental results show vector tracking performing better in multipath environments by several meters.

Second, the range variance parameter is derived as a means to monitor a vector receiver's tracking situation.
Since traditional lock detection does not apply directly to a vector receiver, another approach is needed.
The range variance gives an indication of how the receiver's position uncertainty would translate to range uncertainty.
This is done in a geometry-free way so the receiver can determine the maximum impact its error would have.
The variance parameter is demonstrated in an environment with significant blockage to show its response to the tracking situation.

Third, fault detection and exclusion are applied to a centralized vector tracking architecture.
This integrity method is based on the normalized innovation test parameter.
When new measurements are provided to the navigation filter, they are normalized by their expected variances.
Faulty signals are shown to increase this test parameter and pass the detection threshold.
Live sky demonstrations of fault detection and exclusion yield position improvements on the order of one meter.

Lastly, a deeply integrated GPS/INS algorithm is presented.
The vector fault detection and exclusion method also applies to this fused navigation system.
After dealing with IMU synchronization, results are presented in which an automotive grade IMU is integrated with a vector software receiver.
Using the fault detection and exclusion method, positioning performance is improved by several meters.

In total, this dissertation demonstrates two navigation methods: the GPS vector receiver and the Deeply Integrated GPS/INS system.
Both of these methods are made more robust by performing fault detection and exclusion.
This method is shown to remove velocity drifts and position jumps due to signal errors in difficult scenarios.
The result is a highly robust navigation system for continuous positioning in GPS degraded environments.},
	language = {en},
	urldate = {2024-06-25},
	author = {Clark, Benjamin},
	month = dec,
	year = {2012},
	note = {Accepted: 2012-12-04T15:07:14Z},
}

This dissertation presents a novel fault detection and exclusion method in a centralized deeply integrated GPS/INS navigation system. The method presented is also demonstrated in a centralized vector tracking GPS receiver. Also, a new multipath error model and a range variance parameter are developed to better deal with the additional challenges faced by vector-based receivers. These methods and analysis extend the field of robust navigation, particularly with regards to advanced tracking architectures. GPS was originally designed to operate in clear line of sight view to the supporting satellite constellation. However, recent advances in receiver hardware and computing power have pushed positioning into more difficult scenarios. New ways of using radionavigation sensors, such as vector tracking and deeply integrated GPS/INS, have been developed to handle these situations. However, integrity has been difficult to maintain in these configurations. Fault detection and exclusion can provide this need by keeping the navigation solution free from erroneous measurements that occur in difficult environments. This dissertation presents these contributions in four stages. In the first, a multipath model for vector tracking is developed. This model is based on a delayed signal's interaction with the direct signal correlation peak rather than the scalar early and late correlator outputs. To demonstrate both the model and improved performance of vector tracking, simulated results show the vector receiver tracking the signal with 0.015 m less range error. Experimental results show vector tracking performing better in multipath environments by several meters. Second, the range variance parameter is derived as a means to monitor a vector receiver's tracking situation. Since traditional lock detection does not apply directly to a vector receiver, another approach is needed. The range variance gives an indication of how the receiver's position uncertainty would translate to range uncertainty. This is done in a geometry-free way so the receiver can determine the maximum impact its error would have. The variance parameter is demonstrated in an environment with significant blockage to show its response to the tracking situation. Third, fault detection and exclusion are applied to a centralized vector tracking architecture. This integrity method is based on the normalized innovation test parameter. When new measurements are provided to the navigation filter, they are normalized by their expected variances. Faulty signals are shown to increase this test parameter and pass the detection threshold. Live sky demonstrations of fault detection and exclusion yield position improvements on the order of one meter. Lastly, a deeply integrated GPS/INS algorithm is presented. The vector fault detection and exclusion method also applies to this fused navigation system. After dealing with IMU synchronization, results are presented in which an automotive grade IMU is integrated with a vector software receiver. Using the fault detection and exclusion method, positioning performance is improved by several meters. In total, this dissertation demonstrates two navigation methods: the GPS vector receiver and the Deeply Integrated GPS/INS system. Both of these methods are made more robust by performing fault detection and exclusion. This method is shown to remove velocity drifts and position jumps due to signal errors in difficult scenarios. The result is a highly robust navigation system for continuous positioning in GPS degraded environments.

@unpublished{broderick_dynamic_2012,
	title = {Dynamic {Gaussian} {Process} {Models} for {Model} {Predictive} {Control} of {Vehicle} {Roll}},
	copyright = {EMBARGO\_GLOBAL},
	url = {https://etd.auburn.edu//handle/10415/2982},
	abstract = {The machine learning  method  Gaussian process (GP) regression is used to learn the vehicle dynamics without any prior knowledge.  The model formed with GP regression demonstrates characteristics that make it useful in model predictive control (MPC).  Previous applications of model predictive control used linearized models to balance the need for fast computation and predictive accuracy.  This work aims to make nonlinear predictions in a timely manner.   A method of clustering the training data is also developed in order to further speed calculation of dynamic predictions necessary for MPC.  An architecture to take advantage of the nature of GP regression calculations is then developed.  The efficacy of the approach is examined through training and validation using data recorded from an instrumented all-terrain vehicle (ATV) and through a series of simulations.

The instrumented all-terrain vehicle allowed GPS, inertial, and encoder data to be used for training and validation of the GP-based dynamic model.  A series of maneuvers approximating sinusoids of varying frequency and amplitude is used to excite the vehicle for the purpose of generating a training dataset.  That training dataset allows GP regression to learn the functions describing a nonlinear state-space model of the vehicle dynamics.  The data recorded during a separate set of maneuvers is used to validate the predictions generated from the GP-based model.  The speed of computation is examined and methods of speeding the nonlinear portion of GP regression are presented.  The result of this is a model that can provide accurate estimates in a timely fashion.  The speed of computation is sufficient to allow for MPC to be implemented on a modest, contemporary desktop PC.

A method of further decreasing computation time is then presented.  Clustering of training data has been mentioned in the literature though specifics regarding the choice of algorithm and parameter selection are conspicuously omitted.  Clustering has been applied in the closely related method of support vector machine classification where similarity is easily defined.  A definition of similarity is offered here for the purposes of regression.  An algorithm is selected to leverage that definition of similarity.  Parameter selection is addressed by basing the cluster size on the characteristic length scale of the function being regressed.  Evaluation of the clustering algorithm and parameter is performed on two illustrative examples as well as the GP model formed from the recorded ATV data.},
	language = {en},
	urldate = {2024-06-25},
	author = {Broderick, David},
	month = mar,
	year = {2012},
	note = {Accepted: 2012-03-21T19:07:29Z},
}

The machine learning method Gaussian process (GP) regression is used to learn the vehicle dynamics without any prior knowledge. The model formed with GP regression demonstrates characteristics that make it useful in model predictive control (MPC). Previous applications of model predictive control used linearized models to balance the need for fast computation and predictive accuracy. This work aims to make nonlinear predictions in a timely manner. A method of clustering the training data is also developed in order to further speed calculation of dynamic predictions necessary for MPC. An architecture to take advantage of the nature of GP regression calculations is then developed. The efficacy of the approach is examined through training and validation using data recorded from an instrumented all-terrain vehicle (ATV) and through a series of simulations. The instrumented all-terrain vehicle allowed GPS, inertial, and encoder data to be used for training and validation of the GP-based dynamic model. A series of maneuvers approximating sinusoids of varying frequency and amplitude is used to excite the vehicle for the purpose of generating a training dataset. That training dataset allows GP regression to learn the functions describing a nonlinear state-space model of the vehicle dynamics. The data recorded during a separate set of maneuvers is used to validate the predictions generated from the GP-based model. The speed of computation is examined and methods of speeding the nonlinear portion of GP regression are presented. The result of this is a model that can provide accurate estimates in a timely fashion. The speed of computation is sufficient to allow for MPC to be implemented on a modest, contemporary desktop PC. A method of further decreasing computation time is then presented. Clustering of training data has been mentioned in the literature though specifics regarding the choice of algorithm and parameter selection are conspicuously omitted. Clustering has been applied in the closely related method of support vector machine classification where similarity is easily defined. A definition of similarity is offered here for the purposes of regression. An algorithm is selected to leverage that definition of similarity. Parameter selection is addressed by basing the cluster size on the characteristic length scale of the function being regressed. Evaluation of the clustering algorithm and parameter is performed on two illustrative examples as well as the GP model formed from the recorded ATV data.

@inproceedings{ryan_tire_2012,
	series = {8th {IFAC} {Symposium} on {Fault} {Detection}, {Supervision} and {Safety} of {Technical} {Processes}},
	title = {Tire {Radius} {Determination} and {Pressure} {Loss} {Detection} {Using} {GPS} and {Vehicle} {Stability} {Control} {Sensors}*},
	volume = {45},
	url = {https://www.sciencedirect.com/science/article/pii/S1474667016349187},
	doi = {10.3182/20120829-3-MX-2028.00090},
	abstract = {In this work a method of using GPS and vehicle safety sensors to detect faults in a commercial vehicle are presented. In this case, the fault being detected is a loss of tire pressure. The method uses GPS to detect tire pressure changes and is based on the hypothesis that the effective tire radius varies according to tire pressure. The algorithm, which uses GPS and wheel speed signals to estimate the effective radius of the tires, is discussed and validated in simulation and experiment. The algorithm is based on Kalman filter theory and operates on the assumption that there is no wheel slip, which is valid for the un-driven wheels when the vehicle is not braking. Experiments are given to show how the radius estimate varies according to tire pressure, and a simple pressure loss detection law is presented. Experiments are also shown which illustrate how pressure loss in the driven wheels can be detected even when the no slip assumption is violated.},
	urldate = {2024-06-20},
	booktitle = {{IFAC} {Proceedings} {Volumes}},
	author = {Ryan, Jonathan and Bevly, David},
	month = jan,
	year = {2012},
	keywords = {Filtering and change detection, Filtering and estimation, Mechanical and electro-mechanical applications},
	pages = {1203--1208},
}

In this work a method of using GPS and vehicle safety sensors to detect faults in a commercial vehicle are presented. In this case, the fault being detected is a loss of tire pressure. The method uses GPS to detect tire pressure changes and is based on the hypothesis that the effective tire radius varies according to tire pressure. The algorithm, which uses GPS and wheel speed signals to estimate the effective radius of the tires, is discussed and validated in simulation and experiment. The algorithm is based on Kalman filter theory and operates on the assumption that there is no wheel slip, which is valid for the un-driven wheels when the vehicle is not braking. Experiments are given to show how the radius estimate varies according to tire pressure, and a simple pressure loss detection law is presented. Experiments are also shown which illustrate how pressure loss in the driven wheels can be detected even when the no slip assumption is violated.

@article{dawkins_fractal_2012,
	title = {Fractal terrain generation for vehicle simulation},
	volume = {10},
	issn = {1471-0226, 1741-5306},
	url = {http://www.inderscience.com/link.php?id=47693},
	doi = {10.1504/IJVAS.2012.047693},
	abstract = {This paper presents a methodology for generating rough terrain surfaces for the purpose of vehicle simulation. A 3D Weierstrass-Mandelbrot function was used to generate terrain surfaces with varying roughness. The terrain surfaces were evaluated using the Root Mean Squared Elevation (RMSE), Power Spectral Density (PSD), and International Roughness Index (IRI). Vehicle simulations were conducted at varying speeds on the generated terrains using Carsim, and the vehicle body motions were studied based on Inertial Measurement Unit (IMU) outputs. It was determined that the Weierstrass-Mandelbrot function is an effective way to create simulated surfaces to match a wide range of terrain roughness.},
	language = {en},
	number = {1/2},
	urldate = {2024-06-25},
	journal = {International Journal of Vehicle Autonomous Systems},
	author = {Dawkins, Jeremy J. and Bevly, David M. and Jackson, Robert L.},
	year = {2012},
	pages = {3},
}

This paper presents a methodology for generating rough terrain surfaces for the purpose of vehicle simulation. A 3D Weierstrass-Mandelbrot function was used to generate terrain surfaces with varying roughness. The terrain surfaces were evaluated using the Root Mean Squared Elevation (RMSE), Power Spectral Density (PSD), and International Roughness Index (IRI). Vehicle simulations were conducted at varying speeds on the generated terrains using Carsim, and the vehicle body motions were studied based on Inertial Measurement Unit (IMU) outputs. It was determined that the Weierstrass-Mandelbrot function is an effective way to create simulated surfaces to match a wide range of terrain roughness.

@inproceedings{wang_robust_2012,
	title = {Robust observer design for {Lipschitz} nonlinear systems using quadratic polynomial constraints},
	url = {https://ieeexplore.ieee.org/abstract/document/6426517},
	doi = {10.1109/CDC.2012.6426517},
	abstract = {This paper discusses the observer design for the uncertain Lipschitz nonlinear systems. A new stability analysis method for the Lure problem is first presented. Then, a nonlinear observer is proposed so that the observer error dynamic model can be transformed to an equivalent Lure system in which the input-output relationship of the nonlinear memoryless block is belong to the semi-algebraic set defined by several quadratic polynomial constraints. A sufficient condition for the exponential stability of the observer error dynamics is formulated in terms of the feasibility of linear matrix inequalities (LMIs).},
	urldate = {2024-06-20},
	booktitle = {2012 {IEEE} 51st {IEEE} {Conference} on {Decision} and {Control} ({CDC})},
	author = {Wang, Yan and Bevly, David M.},
	month = dec,
	year = {2012},
	note = {ISSN: 0743-1546},
	keywords = {Asymptotic stability, Mathematical model, Observers, Polynomials, Stability criteria, Vectors},
	pages = {6621--6626},
}

This paper discusses the observer design for the uncertain Lipschitz nonlinear systems. A new stability analysis method for the Lure problem is first presented. Then, a nonlinear observer is proposed so that the observer error dynamic model can be transformed to an equivalent Lure system in which the input-output relationship of the nonlinear memoryless block is belong to the semi-algebraic set defined by several quadratic polynomial constraints. A sufficient condition for the exponential stability of the observer error dynamics is formulated in terms of the feasibility of linear matrix inequalities (LMIs).

@inproceedings{payne_control_2012,
	title = {Control of a robot-trailer system using a single non-collocated sensor},
	url = {https://ieeexplore.ieee.org/document/6389154/;jsessionid=3A452369700DE58F1D8B76CA270E5AA8},
	doi = {10.1109/IECON.2012.6389154},
	abstract = {In this paper, the authors develop an observer and controller for a robot and trailer system in which only a single non-collocated position measurement is used. A linearized state-space model of the system is derived using kinematic equations that have previously proven sufficient for state feedback control. Optimal observer gains (LQG) and controller gains (LQR) are calculated using known process and measurement noise variances. Simulations and experiments both confirm that the LQG/LQR system controls the nonlinear system in path tracking. Control based on state estimation yields performance that is comparable to a more heavily-instrumented full-state feedback system previously used on the robot-trailer system.},
	urldate = {2024-06-20},
	booktitle = {{IECON} 2012 - 38th {Annual} {Conference} on {IEEE} {Industrial} {Electronics} {Society}},
	author = {Payne, Michael L. and Hung, John Y. and Bevly, David M. and Selfridge, Bob J.},
	month = oct,
	year = {2012},
	note = {ISSN: 1553-572X},
	keywords = {Aerospace electronics, Mathematical model, Robot sensing systems, Sensor arrays, Service robots, Vehicles},
	pages = {2674--2679},
}

In this paper, the authors develop an observer and controller for a robot and trailer system in which only a single non-collocated position measurement is used. A linearized state-space model of the system is derived using kinematic equations that have previously proven sufficient for state feedback control. Optimal observer gains (LQG) and controller gains (LQR) are calculated using known process and measurement noise variances. Simulations and experiments both confirm that the LQG/LQR system controls the nonlinear system in path tracking. Control based on state estimation yields performance that is comparable to a more heavily-instrumented full-state feedback system previously used on the robot-trailer system.

@inproceedings{martin_performance_2012,
	title = {Performance analysis of a scalable navigation solution using vehicle safety sensors},
	url = {https://ieeexplore.ieee.org/document/6232286/;jsessionid=6B56F7C58B4170BEFCF36C0B4BDDCA02},
	doi = {10.1109/IVS.2012.6232286},
	abstract = {GPS receiver performance can suffer in difficult environments such as urban canyons and heavy foliage. Inertial sensors provide information between GPS updates and can enhance the position solution in a GPS/INS architecture. Additional information from safety sensors already on the vehicle, such as lane departure warning (LDW) sensors, can enhance the navigation solution further by constraining inertial errors even in the presence of GPS errors. This paper outlines a scalable navigation solution that can use a combination of GPS, reduced inertial sensors, full inertial data, vehicle CAN data, and vision sensors, depending on what data is available in difficult environments. Data was collected in Detroit, Michigan in a diverse mix of environments that includes heavy foliage, highway, and downtown areas, in proportions representative of what is expected in typical driving. Validation of the approach consists of both a qualitative analysis of the resulting trajectories overlaid on a map of the area and quantitative comparison of the trajectories produced by the proposed system and the reference system.},
	urldate = {2024-06-20},
	booktitle = {2012 {IEEE} {Intelligent} {Vehicles} {Symposium}},
	author = {Martin, S. and Rose, C. and Britt, J. and Bevly, D. and Popovic, Zeljko},
	month = jun,
	year = {2012},
	note = {ISSN: 1931-0587},
	keywords = {Cameras, GPS, Global Positioning System, IMU, INS, Laser radar, Sensors, Vehicles, Wheels, camera, foliage, inertial, lidar, localization, navigation, positioning, sensor fusion, urban canyon, vision},
	pages = {926--931},
}

GPS receiver performance can suffer in difficult environments such as urban canyons and heavy foliage. Inertial sensors provide information between GPS updates and can enhance the position solution in a GPS/INS architecture. Additional information from safety sensors already on the vehicle, such as lane departure warning (LDW) sensors, can enhance the navigation solution further by constraining inertial errors even in the presence of GPS errors. This paper outlines a scalable navigation solution that can use a combination of GPS, reduced inertial sensors, full inertial data, vehicle CAN data, and vision sensors, depending on what data is available in difficult environments. Data was collected in Detroit, Michigan in a diverse mix of environments that includes heavy foliage, highway, and downtown areas, in proportions representative of what is expected in typical driving. Validation of the approach consists of both a qualitative analysis of the resulting trajectories overlaid on a map of the area and quantitative comparison of the trajectories produced by the proposed system and the reference system.

@inproceedings{wang_lateral_2012,
	address = {Fort Lauderdale, Florida, USA},
	title = {Lateral {Tire} {Force} {Estimation} {With} {Unknown} {Input} {Observer}},
	isbn = {978-0-7918-4531-8},
	url = {http://proceedings.asmedigitalcollection.asme.org/proceeding.aspx?doi=10.1115/DSCC2012-MOVIC2012-8712},
	doi = {10.1115/DSCC2012-MOVIC2012-8712},
	urldate = {2024-06-20},
	booktitle = {Volume 3: {Renewable} {Energy} {Systems}; {Robotics}; {Robust} {Control}; {Single} {Track} {Vehicle} {Dynamics} and {Control}; {Stochastic} {Models}, {Control} and {Algorithms} in {Robotics}; {Structure} {Dynamics} and {Smart} {Structures};},
	publisher = {ASME},
	author = {Wang, Yan and Bevly, David M. and Chen, Shih-ken},
	month = oct,
	year = {2012},
	pages = {531--538},
}

@inproceedings{wang_longitudinal_2012,
	address = {Fort Lauderdale, Florida, USA},
	title = {Longitudinal {Tire} {Force} {Estimation} {With} {Unknown} {Input} {Observer}},
	isbn = {978-0-7918-4531-8},
	url = {http://proceedings.asmedigitalcollection.asme.org/proceeding.aspx?doi=10.1115/DSCC2012-MOVIC2012-8710},
	doi = {10.1115/DSCC2012-MOVIC2012-8710},
	urldate = {2024-06-20},
	booktitle = {Volume 3: {Renewable} {Energy} {Systems}; {Robotics}; {Robust} {Control}; {Single} {Track} {Vehicle} {Dynamics} and {Control}; {Stochastic} {Models}, {Control} and {Algorithms} in {Robotics}; {Structure} {Dynamics} and {Smart} {Structures};},
	publisher = {ASME},
	author = {Wang, Yan and Bevly, David M. and Chen, Shih-ken},
	month = oct,
	year = {2012},
	pages = {523--530},
}

@inproceedings{ryan_robust_2012,
	title = {Robust {Ground} {Vehicle} {Constraints} for {Aiding} {Stand} {Alone} {INS} and {Determining} {Inertial} {Sensor} {Errors}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=9979},
	abstract = {Ground vehicle velocity constraints are commonly used to aid inertial navigation systems (INS) in land vehicle applications, especially in the absence of other external aiding sensors such as GPS. It is common to make the assumption that the lateral velocity of the vehicle in the frame of the road surface is zero, and that the vertical velocity in this frame is also zero. The latter assumption practically means that the vehicle does not leave the ground, which is reasonable for the vast majority of applications. However the former assumption means that the vehicle is not sliding, or that that there is no sideslip. While there are many operating conditions for which this assumption is valid, there are also many scenarios for which this assumption is violated. Such violations introduce error into the navigation solution and can be especially problematic when no external aiding to the inertial measurement unit (IMU) is available. This paper examines the errors in an unaided INS navigation solution caused by violating the lateral assumption and introduces a method of detecting when the constraint is violated. This allows for a best of both worlds solution in which the benefits of the aiding constraint can be taken advantage of when the constraint is valid without introducing errors when it is not valid. First, experiments are conducted using Carsim, a high fidelity commercial vehicle simulation package. The relative positioning performance when using different approaches for the lateral constraint is analyzed. Additionally, data collected from an electric all terrain vehicle (ATV) which instrumented with various sensors, is used to validate the conclusions. Finally, the velocity constraints are used to estimate biases in the lateral and vertical accelerometers. Results based on both the real world and simulated experiments are discussed.},
	language = {en},
	urldate = {2024-06-20},
	author = {Ryan, J. and Bevly, D.},
	month = feb,
	year = {2012},
	pages = {374--401},
}

Ground vehicle velocity constraints are commonly used to aid inertial navigation systems (INS) in land vehicle applications, especially in the absence of other external aiding sensors such as GPS. It is common to make the assumption that the lateral velocity of the vehicle in the frame of the road surface is zero, and that the vertical velocity in this frame is also zero. The latter assumption practically means that the vehicle does not leave the ground, which is reasonable for the vast majority of applications. However the former assumption means that the vehicle is not sliding, or that that there is no sideslip. While there are many operating conditions for which this assumption is valid, there are also many scenarios for which this assumption is violated. Such violations introduce error into the navigation solution and can be especially problematic when no external aiding to the inertial measurement unit (IMU) is available. This paper examines the errors in an unaided INS navigation solution caused by violating the lateral assumption and introduces a method of detecting when the constraint is violated. This allows for a best of both worlds solution in which the benefits of the aiding constraint can be taken advantage of when the constraint is valid without introducing errors when it is not valid. First, experiments are conducted using Carsim, a high fidelity commercial vehicle simulation package. The relative positioning performance when using different approaches for the lateral constraint is analyzed. Additionally, data collected from an electric all terrain vehicle (ATV) which instrumented with various sensors, is used to validate the conclusions. Finally, the velocity constraints are used to estimate biases in the lateral and vertical accelerometers. Results based on both the real world and simulated experiments are discussed.

@inproceedings{woodall_using_2012,
	title = {Using the microsoft kinect for {3D} map building and teleoperation},
	url = {https://ieeexplore.ieee.org/document/6236847/;jsessionid=D6461699FC4F0C99E1C538444AD31665},
	doi = {10.1109/PLANS.2012.6236847},
	abstract = {This paper describes the use of the Microsoft Kinect for building three dimensional maps for use in teleoperation. Though these maps are being used for teleoperation in this paper, these map building techniques could also be applied in localization for navigation or robot path planning. The Kinect is a relatively new depth sensor that has become popular in the field of robotics, often replacing significantly more expensive systems like tilting laser range finders and stereoscopic vision systems. Two main sources of error in the map making are investigated, random and systematic error from the depth sensor and uncertainty in the navigation solution of the vehicle. Systematic and random error in the Kinect has previously been described in the literature [1] and this paper looks at how these errors affect the users ability to do mapping and offers some practical solutions. The teleoperation system design around this map making process is presented, and it builds on existing work [2] using octrees as the storage for the maps.},
	urldate = {2024-06-20},
	booktitle = {Proceedings of the 2012 {IEEE}/{ION} {Position}, {Location} and {Navigation} {Symposium}},
	author = {Woodall, William J. and Bevly, David},
	month = apr,
	year = {2012},
	note = {ISSN: 2153-3598},
	keywords = {Artificial neural networks, Indium phosphide, Kinect, Mapping, Octree, Robotics, Robots, Stereo image processing, Teleoperation},
	pages = {1054--1061},
}

This paper describes the use of the Microsoft Kinect for building three dimensional maps for use in teleoperation. Though these maps are being used for teleoperation in this paper, these map building techniques could also be applied in localization for navigation or robot path planning. The Kinect is a relatively new depth sensor that has become popular in the field of robotics, often replacing significantly more expensive systems like tilting laser range finders and stereoscopic vision systems. Two main sources of error in the map making are investigated, random and systematic error from the depth sensor and uncertainty in the navigation solution of the vehicle. Systematic and random error in the Kinect has previously been described in the literature [1] and this paper looks at how these errors affect the users ability to do mapping and offers some practical solutions. The teleoperation system design around this map making process is presented, and it builds on existing work [2] using octrees as the storage for the maps.

@article{martin_comparison_2012,
	title = {Comparison of {GPS}-based autonomous vehicle following using global and relative positioning},
	volume = {10},
	issn = {1471-0226, 1741-5306},
	url = {http://www.inderscience.com/link.php?id=51245},
	doi = {10.1504/IJVAS.2012.051245},
	language = {en},
	number = {3},
	urldate = {2024-06-20},
	journal = {International Journal of Vehicle Autonomous Systems},
	author = {Martin, Scott and Bevly, David M.},
	year = {2012},
	pages = {229},
}

@unpublished{ryan_fully_2011,
	type = {thesis},
	title = {A {Fully} {Integrated} {Sensor} {Fusion} {Method} {Combining} a {Single} {Antenna} {GPS} {Unit} with {Electronic} {Stability} {Control} {Sensors}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/2655},
	abstract = {This work presents a method for incorporating GPS (Global Positioning System) and standard roll stability control (RSC) sensors into the electronic stability control (ESC) and RSC systems.  It is an adaptation of the very well known loosely-coupled GPS/INS (Inertial Navigation System) integration strategy which has been modified for the purposes of ESC systems. The first modification is the removal of the pitch rate gyroscope, a sensor which is unavailable on commercial vehicles. The second modification deals with the observability problems of the standard loosely coupled filter by adding heading constraints when the vehicle is not turning. The structure and algorithm of this method is presented. Observability conditions are evaluated, and the convergence of the estimates are analyzed via simulations. The conclusions from these simulations are compared with the expectations from the literature and observability condition checks. An experiment which illustrates the long term performance of the bias estimation was performed, followed by an experiment showing the roll and sideslip estimation performance during dynamic events. It is shown that over the long term the inertial bias estimates will converge if the vehicle experiences adequate dynamics, and that the system is able to accurately estimate sideslip and roll during dynamic maneuvers. The system is also able to estimate slow sideslip buildup, an important capability for ESC systems. The unified system is compared with a less integrated or ''modular'' approach for both experiments.

Furthermore, a method for using GPS to detect tire pressure changes is presented based on the hypothesis that the tire effective radius varies according to tire pressure. A technique using GPS and wheel speed signals to estimate the effective radius of the tires is discussed and validated in simulation and experiment. Experiments are given to show how the radius estimate varies according to tire pressure, and a simple pressure loss detection law is discussed. A method to detect steering misalignment is also presented.},
	language = {en},
	urldate = {2024-06-25},
	author = {Ryan, Jonathan},
	month = jul,
	year = {2011},
	note = {Accepted: 2011-07-05T19:31:32Z},
}

This work presents a method for incorporating GPS (Global Positioning System) and standard roll stability control (RSC) sensors into the electronic stability control (ESC) and RSC systems. It is an adaptation of the very well known loosely-coupled GPS/INS (Inertial Navigation System) integration strategy which has been modified for the purposes of ESC systems. The first modification is the removal of the pitch rate gyroscope, a sensor which is unavailable on commercial vehicles. The second modification deals with the observability problems of the standard loosely coupled filter by adding heading constraints when the vehicle is not turning. The structure and algorithm of this method is presented. Observability conditions are evaluated, and the convergence of the estimates are analyzed via simulations. The conclusions from these simulations are compared with the expectations from the literature and observability condition checks. An experiment which illustrates the long term performance of the bias estimation was performed, followed by an experiment showing the roll and sideslip estimation performance during dynamic events. It is shown that over the long term the inertial bias estimates will converge if the vehicle experiences adequate dynamics, and that the system is able to accurately estimate sideslip and roll during dynamic maneuvers. The system is also able to estimate slow sideslip buildup, an important capability for ESC systems. The unified system is compared with a less integrated or ''modular'' approach for both experiments. Furthermore, a method for using GPS to detect tire pressure changes is presented based on the hypothesis that the tire effective radius varies according to tire pressure. A technique using GPS and wheel speed signals to estimate the effective radius of the tires is discussed and validated in simulation and experiment. Experiments are given to show how the radius estimate varies according to tire pressure, and a simple pressure loss detection law is discussed. A method to detect steering misalignment is also presented.

@unpublished{martin_closely_2011,
	type = {thesis},
	title = {Closely {Coupled} {GPS}/{INS} {Relative} {Positioning} {For} {Automated} {Vehicle} {Convoys}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/2533},
	abstract = {In this thesis, differential GPS methods are developed for use in automated vehicle convoy positioning. The GPS pseudorange and carrier phase measurements are used to compute relative position vectors between two vehicles with sub-meter errors. It is the carrier phase measurement that makes this level of accuracy attainable but the carrier phase ambiguity must be resolved prior to the relative position estimation. An algorithm, referred to as Dynamic base Real Time Kinematic (DRTK) algorithm, is described in this thesis to estimate the carrier phase ambiguity and the relative position vector between two GPS receivers. The DRTK algorithm is capable of using single frequency (L1 or L2 frequency only) or dual frequency (L1 and L2 frequency) GPS measurements to estimate the relative position vector. A comparative study of the performance of the algorithm using either single or dual frequency measurements is presented.

The DRTK algorithm is expanded to incorporate inertial measurement to increase to output rate, to improve solution availability, and to improve the reliability of the algorithm. Since inertial navigation systems (INS) compute a navigation solution independent of any additional infrastructure, the INS can be used to update the relative position vector estimate during short GPS outages. The update rate of the INS is also as much as ten times the rate of the GPS receiver meaning that the integrated system produces estimates at a significantly higher output rate. The combined DRTK/INS system is implemented with two integration architectures -- a federated GPS/INS/DRTK architecture and a centralized DRTK/INS architecture. Each configuration produced estimates of the relative position vector with error on the centimeter level.

Finally, the use of relative positioning to autonomously follow a human driven lead vehicle is presented. Time difference carrier phase (TDCP) measurements are used to estimate the change in the position of the following vehicle between measurement epochs. The TDCP algorithm is combined with the DRTK algorithm to estimate the position of the following vehicle relative to a virtual lead vehicle position. Analysis of the accuracy of the TDCP algorithm at individual measurement epochs and over varying time intervals is presented. The DRTK/TDCP following method is compared to a GPS waypoint following method using data collected on an automated all-terrain vehicle.},
	language = {en},
	urldate = {2024-06-25},
	author = {Martin, Scott},
	month = apr,
	year = {2011},
	note = {Accepted: 2011-04-15T14:18:41Z},
}

In this thesis, differential GPS methods are developed for use in automated vehicle convoy positioning. The GPS pseudorange and carrier phase measurements are used to compute relative position vectors between two vehicles with sub-meter errors. It is the carrier phase measurement that makes this level of accuracy attainable but the carrier phase ambiguity must be resolved prior to the relative position estimation. An algorithm, referred to as Dynamic base Real Time Kinematic (DRTK) algorithm, is described in this thesis to estimate the carrier phase ambiguity and the relative position vector between two GPS receivers. The DRTK algorithm is capable of using single frequency (L1 or L2 frequency only) or dual frequency (L1 and L2 frequency) GPS measurements to estimate the relative position vector. A comparative study of the performance of the algorithm using either single or dual frequency measurements is presented. The DRTK algorithm is expanded to incorporate inertial measurement to increase to output rate, to improve solution availability, and to improve the reliability of the algorithm. Since inertial navigation systems (INS) compute a navigation solution independent of any additional infrastructure, the INS can be used to update the relative position vector estimate during short GPS outages. The update rate of the INS is also as much as ten times the rate of the GPS receiver meaning that the integrated system produces estimates at a significantly higher output rate. The combined DRTK/INS system is implemented with two integration architectures – a federated GPS/INS/DRTK architecture and a centralized DRTK/INS architecture. Each configuration produced estimates of the relative position vector with error on the centimeter level. Finally, the use of relative positioning to autonomously follow a human driven lead vehicle is presented. Time difference carrier phase (TDCP) measurements are used to estimate the change in the position of the following vehicle between measurement epochs. The TDCP algorithm is combined with the DRTK algorithm to estimate the position of the following vehicle relative to a virtual lead vehicle position. Analysis of the accuracy of the TDCP algorithm at individual measurement epochs and over varying time intervals is presented. The DRTK/TDCP following method is compared to a GPS waypoint following method using data collected on an automated all-terrain vehicle.

@unpublished{jantz_controlling_2011,
	type = {thesis},
	title = {Controlling the {Speed} of a {Magnetically}-{Suspended} {Rotor} with {Compressed} {Air}},
	url = {https://etd.auburn.edu//handle/10415/2521},
	abstract = {Magnetic bearing research is generally concerned with the development of the automatic control systems required to levitate a rotor, driven by either an electric motor or air turbine. The regulation of rotor speed in research has often been accomplished by manual methods, turning a rheostat in the case of an electric motor and by adjusting a regulator or valve if the drive is by an air turbine.
Automatic control of rotor speed would facilitate research using magnetic bearings. This control would assist the development of adaptive disturbance rejection techniques since rotor speed could be easily adjusted for any change in the desired rejection frequency. Automatic speed control could also be central to health and containment strategies for magnetically suspended flywheels used in the control of space structures. If cracks are detected in a flywheel through health monitoring, the speed of the rotor/flywheel could be automatically reduced to a level where the damaged flywheel could be temporarily operated.
This work details the development and implementation of a control system to automatically and precisely regulate the speed of a magnetically suspended rotor and flywheel. Development began with the installation of an electronic flow control valve and all instrumentation needed to measure rotor response. Once all hardware was in place, a Simulink model of the entire system, actuator (electronic valve) and plant (air turbine, magnetic bearings, rotor and flywheel), was created. This model was developed using system identification techniques where a step input is applied to the plant and its response is measured. A transfer function of the plant was derived from these tests, and it relates volumetric flow rate of air to rotor speed and uses variable coefficients. The operation of the electronic valve was too complex to be described by differential equations or transfer functions. Thus, a model of it was written in software and included in Simulink using an embedded MATLAB function.
 
The Simulink model was then used to develop a speed controller for the simulated system. Simulations established the type of controller and its gains. A proportional-derivative or PD controller was found to accurately regulate the speed of the simulated system. When complete, this controller was combined with the actual magnetic-bearing controller to create the software necessary for bearing and speed control. This software was then executed on dSPACE hardware to provide overall control of the system - actuator, bearings, rotor and flywheel. Numerous tests were conducted on this system to tune the gains of the speed controller. Once tuned, the PD controller developed in the simulated environment worked exceptionally well on the real system. The controller can maintain the actual speed of the rotor to within a few rpm of the desired for speeds ranging from 200 to over 6000 rpm.
The final part of this work involved developing instrument panels from which to operate the bearings and control the speed of the rotor. Instrument panels similar to those found in automobiles were created using ControlDesk, an integrated software development environment provided with dSPACE. A series of panels were designed and created so that variables necessary to operate and precisely control the bearings and rotor could be monitored and easily adjusted.},
	language = {en},
	urldate = {2024-06-25},
	author = {Jantz, Robert},
	month = apr,
	year = {2011},
	note = {Accepted: 2011-04-08T19:32:19Z},
}

Magnetic bearing research is generally concerned with the development of the automatic control systems required to levitate a rotor, driven by either an electric motor or air turbine. The regulation of rotor speed in research has often been accomplished by manual methods, turning a rheostat in the case of an electric motor and by adjusting a regulator or valve if the drive is by an air turbine. Automatic control of rotor speed would facilitate research using magnetic bearings. This control would assist the development of adaptive disturbance rejection techniques since rotor speed could be easily adjusted for any change in the desired rejection frequency. Automatic speed control could also be central to health and containment strategies for magnetically suspended flywheels used in the control of space structures. If cracks are detected in a flywheel through health monitoring, the speed of the rotor/flywheel could be automatically reduced to a level where the damaged flywheel could be temporarily operated. This work details the development and implementation of a control system to automatically and precisely regulate the speed of a magnetically suspended rotor and flywheel. Development began with the installation of an electronic flow control valve and all instrumentation needed to measure rotor response. Once all hardware was in place, a Simulink model of the entire system, actuator (electronic valve) and plant (air turbine, magnetic bearings, rotor and flywheel), was created. This model was developed using system identification techniques where a step input is applied to the plant and its response is measured. A transfer function of the plant was derived from these tests, and it relates volumetric flow rate of air to rotor speed and uses variable coefficients. The operation of the electronic valve was too complex to be described by differential equations or transfer functions. Thus, a model of it was written in software and included in Simulink using an embedded MATLAB function. The Simulink model was then used to develop a speed controller for the simulated system. Simulations established the type of controller and its gains. A proportional-derivative or PD controller was found to accurately regulate the speed of the simulated system. When complete, this controller was combined with the actual magnetic-bearing controller to create the software necessary for bearing and speed control. This software was then executed on dSPACE hardware to provide overall control of the system - actuator, bearings, rotor and flywheel. Numerous tests were conducted on this system to tune the gains of the speed controller. Once tuned, the PD controller developed in the simulated environment worked exceptionally well on the real system. The controller can maintain the actual speed of the rotor to within a few rpm of the desired for speeds ranging from 200 to over 6000 rpm. The final part of this work involved developing instrument panels from which to operate the bearings and control the speed of the rotor. Instrument panels similar to those found in automobiles were created using ControlDesk, an integrated software development environment provided with dSPACE. A series of panels were designed and created so that variables necessary to operate and precisely control the bearings and rotor could be monitored and easily adjusted.

@unpublished{green_non-contact_2011,
	type = {thesis},
	title = {A {Non}-contact {Method} for {Sensing} {Tire} {Contact} {Patch} {Deformation} {Using} a {Monocular} {Vision} {System} and {Speckled} {Image} {Tracking}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/2630},
	abstract = {A full-field, non-contact deformation sensing system was developed with an application for tires. Using an image tracking algorithm, in-plane displacements and their gradients were calculated. Furthermore, the effects of blurring from out-of-plane displacement and illumination variation were included in the algorithm developed, providing more accurate in-plane information. An imaging system was placed inside a tire that was compressed by approximate normal loadings. Images of the compressed inner liner were recorded and processed. Although a lens defect made independent determination of the out-of-plane displacement to blurring relationship impossible, an assumption was made given the normal loading condition that allowed normal strains to be plotted at six increments of vertical deflection. The longitudinal strain distribution shows an interesting behavior hardly noted in most literature although the tensile strain does generally increase with increasing load. Having proved that digital image processing can measure tire deformation accurately, this research should provide a solid foundation to develop the technique presented into more robust and efficient forms. With improvements, this technology could be implemented in real automotives to provide the high fidelity information needed to derive accurate tire parameters for advanced electronic stability control systems.},
	language = {en},
	urldate = {2024-06-25},
	author = {Green, Russell},
	month = may,
	year = {2011},
	note = {Accepted: 2011-05-16T17:48:46Z},
}

A full-field, non-contact deformation sensing system was developed with an application for tires. Using an image tracking algorithm, in-plane displacements and their gradients were calculated. Furthermore, the effects of blurring from out-of-plane displacement and illumination variation were included in the algorithm developed, providing more accurate in-plane information. An imaging system was placed inside a tire that was compressed by approximate normal loadings. Images of the compressed inner liner were recorded and processed. Although a lens defect made independent determination of the out-of-plane displacement to blurring relationship impossible, an assumption was made given the normal loading condition that allowed normal strains to be plotted at six increments of vertical deflection. The longitudinal strain distribution shows an interesting behavior hardly noted in most literature although the tensile strain does generally increase with increasing load. Having proved that digital image processing can measure tire deformation accurately, this research should provide a solid foundation to develop the technique presented into more robust and efficient forms. With improvements, this technology could be implemented in real automotives to provide the high fidelity information needed to derive accurate tire parameters for advanced electronic stability control systems.

@unpublished{allen_ues_2011,
	type = {thesis},
	title = {Ues of {Vision} {Sensors} and {Lane} {Maps} to {Aid} {GPS}-{INS} {Navigation}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/2807},
	abstract = {This thesis proposes a method to increase observability of a GPS/INS system operating under limited satellite coverage. Measurements from vision sensors are used to supplement the GPS pseudorange and pseudorange-rate measurements. Both LiDAR and camera measurements are used to measure the lateral position of a vehicle in its current lane. The vision measurements provide local based positioning based off the lane. A map of the lane is used to relate the local position measurement provided by the vision systems to the global coordinate frame used by GPS and the navigation filter. Since the filter is used for ground vehicles, the height above the ground is constant. The constant height can be used to constrain position in another axis that is orthogonal to the axis in which lane position measurements are given.

In order to test the performance of the navigation filter, real data from the NCAT test track in Opelika, Alabama will be used. RTK GPS is used as a "truth" metric in order to determine filter performance. Experimental results show that using vision measurements with a precise lane map results in centimeter level global accuracy in the axis perpendicular to the road and meter level (depending on the quality of GPS measurements available) global accuracy in the axis parallel with the road. It is also shown that the navigation filter remains observable and functional if two GPS observations along with vision measurement and a lane map are available. The results also show a reduction in position drift when GPS is unavailable if vision measurements and a lane map are available.},
	language = {en},
	urldate = {2024-06-25},
	author = {Allen, John},
	month = aug,
	year = {2011},
	note = {Accepted: 2011-08-25T18:08:44Z},
}

This thesis proposes a method to increase observability of a GPS/INS system operating under limited satellite coverage. Measurements from vision sensors are used to supplement the GPS pseudorange and pseudorange-rate measurements. Both LiDAR and camera measurements are used to measure the lateral position of a vehicle in its current lane. The vision measurements provide local based positioning based off the lane. A map of the lane is used to relate the local position measurement provided by the vision systems to the global coordinate frame used by GPS and the navigation filter. Since the filter is used for ground vehicles, the height above the ground is constant. The constant height can be used to constrain position in another axis that is orthogonal to the axis in which lane position measurements are given. In order to test the performance of the navigation filter, real data from the NCAT test track in Opelika, Alabama will be used. RTK GPS is used as a "truth" metric in order to determine filter performance. Experimental results show that using vision measurements with a precise lane map results in centimeter level global accuracy in the axis perpendicular to the road and meter level (depending on the quality of GPS measurements available) global accuracy in the axis parallel with the road. It is also shown that the navigation filter remains observable and functional if two GPS observations along with vision measurement and a lane map are available. The results also show a reduction in position drift when GPS is unavailable if vision measurements and a lane map are available.

@unpublished{ma_modeling_2011,
	title = {Modeling, {Machine} {Vision} {Sensing} and {Material} {Flow} {System} {Definition} of {Braiding} {Point} {Motion}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/2478},
	abstract = {This dissertation is focused on the modeling of one kind of braiding machine and its key part, the carrier. The carrier is a small mass-spring-damping tensioning system, which defines the characteristics and response of the braiding point on an operating braiding machine.   The yarn tension from a carrier versus displacement characteristic is first derived, and experimentally verified.   Based on this result, the braiding point motion envelop is investigated in order to determine and explain the expected range of small braid point motion and oscillation that occur about the steady state. A material flow system model is derived for the braiding process at the braiding point. Three mathematical models are created and combined to form an integrated model of the entire braiding process. Using machine vision routines developed in this dissertation, a control program was used to monitor and record the braiding point motion and compare it with analytical results. A new noninvasive machine vision sensor was developed, for use with a piecewise PI controller on a separate take up motor using the position data acquired from a machine vision sensing loop. Correlated experiment and simulation response validate the mathematical model, which is similar to a first order liquid level system.  
            Braiding is a manufacturing process for making tubular products. A yarn or tow tensioning system, a carrier, is required that consists of two small pulleys, two springs and a ratchet with the ratchet gear on the spool with wound yarn. The tension coming from a single carrier is nearly constant, varying within an acceptable range during braided product formation and releasing a discrete amount of material from a spool when an upper limit on the tension is reached. The releasing frequency depends on the towed speed of the yarn. A mathematical model of tension versus yarn displacement of a standard package tensioning system is presented. The response before ratchet release is a series of piecewise linear kinematic regions that include two separate spring preload regions, a single spring tensioning region, and a two spring tensioning regions. During the ratchet releasing, the system is modeled as two regions of a single degree-of-freedom dynamic model, releasing region and impact region. Ratchet reengagement that incorporated impact with an elastic yarn was required to improve model accuracy of response. 
           The 32-carrier braiding machine used in this dissertation included a braiding motor, a take up motor and 32 carriers with corresponding yarns. The tension coming from single yarn is nearly constant, especially, when compared with the tension of the rope towed by the take up motor during the braiding process. The length of material releasing from the carriers affects the motion of braiding point. The tension of a single yarn changes because of yarn releasing.  The releasing materials and releasing tension of the yarn cause the oscillation of the braiding point. A mathematical model of the braiding process close to the braiding point region is presented as a quasistatic process. The response after ratchet release is shown to be the reason for oscillation of the braiding point in the steady state. The amount released determines the maximum range of the locus of the braiding point. And the releasing frequency determines the frequency of oscillation. The locus of the braiding point moves on an “ellipsoidal cap”. Since the releasing of yarn is almost instantaneous, the motion of braiding point rapidly jumps from one point to another.
            Controlling braiding angle is important for controlling the quality of braiding products. Controlling the position of the braiding point also controls the braiding angle. In practice, it takes a long time for a braiding point to find its steady state position after startup (if the two motor keep a constant speed). This can lead to a large amount of wasted material and lost production.  The braiding point pattern includes 32 yarns, rope and the convergent zone. This machine vision pattern, viewed with a USB camera, changes from moment to moment during braiding process. Setting up the corresponding threshold for pattern change is important, and is based on the color of yarn and lighting condition (illumination) of the background. The machine vision algorithm senses the braiding point using the geometric pattern matching method in Labview.  The PI controller is designed to drive the take up motor in order to reduce the settling time of the braiding point, using a feedback position signal from the machine vision system.  Experimental results confirms this technique to substantially reduce the amount of material waste.},
	language = {en},
	urldate = {2024-06-25},
	author = {Ma, Guangli},
	month = feb,
	year = {2011},
	note = {Accepted: 2011-02-03T17:44:04Z},
}

This dissertation is focused on the modeling of one kind of braiding machine and its key part, the carrier. The carrier is a small mass-spring-damping tensioning system, which defines the characteristics and response of the braiding point on an operating braiding machine. The yarn tension from a carrier versus displacement characteristic is first derived, and experimentally verified. Based on this result, the braiding point motion envelop is investigated in order to determine and explain the expected range of small braid point motion and oscillation that occur about the steady state. A material flow system model is derived for the braiding process at the braiding point. Three mathematical models are created and combined to form an integrated model of the entire braiding process. Using machine vision routines developed in this dissertation, a control program was used to monitor and record the braiding point motion and compare it with analytical results. A new noninvasive machine vision sensor was developed, for use with a piecewise PI controller on a separate take up motor using the position data acquired from a machine vision sensing loop. Correlated experiment and simulation response validate the mathematical model, which is similar to a first order liquid level system. Braiding is a manufacturing process for making tubular products. A yarn or tow tensioning system, a carrier, is required that consists of two small pulleys, two springs and a ratchet with the ratchet gear on the spool with wound yarn. The tension coming from a single carrier is nearly constant, varying within an acceptable range during braided product formation and releasing a discrete amount of material from a spool when an upper limit on the tension is reached. The releasing frequency depends on the towed speed of the yarn. A mathematical model of tension versus yarn displacement of a standard package tensioning system is presented. The response before ratchet release is a series of piecewise linear kinematic regions that include two separate spring preload regions, a single spring tensioning region, and a two spring tensioning regions. During the ratchet releasing, the system is modeled as two regions of a single degree-of-freedom dynamic model, releasing region and impact region. Ratchet reengagement that incorporated impact with an elastic yarn was required to improve model accuracy of response. The 32-carrier braiding machine used in this dissertation included a braiding motor, a take up motor and 32 carriers with corresponding yarns. The tension coming from single yarn is nearly constant, especially, when compared with the tension of the rope towed by the take up motor during the braiding process. The length of material releasing from the carriers affects the motion of braiding point. The tension of a single yarn changes because of yarn releasing. The releasing materials and releasing tension of the yarn cause the oscillation of the braiding point. A mathematical model of the braiding process close to the braiding point region is presented as a quasistatic process. The response after ratchet release is shown to be the reason for oscillation of the braiding point in the steady state. The amount released determines the maximum range of the locus of the braiding point. And the releasing frequency determines the frequency of oscillation. The locus of the braiding point moves on an “ellipsoidal cap”. Since the releasing of yarn is almost instantaneous, the motion of braiding point rapidly jumps from one point to another. Controlling braiding angle is important for controlling the quality of braiding products. Controlling the position of the braiding point also controls the braiding angle. In practice, it takes a long time for a braiding point to find its steady state position after startup (if the two motor keep a constant speed). This can lead to a large amount of wasted material and lost production. The braiding point pattern includes 32 yarns, rope and the convergent zone. This machine vision pattern, viewed with a USB camera, changes from moment to moment during braiding process. Setting up the corresponding threshold for pattern change is important, and is based on the color of yarn and lighting condition (illumination) of the background. The machine vision algorithm senses the braiding point using the geometric pattern matching method in Labview. The PI controller is designed to drive the take up motor in order to reduce the settling time of the braiding point, using a feedback position signal from the machine vision system. Experimental results confirms this technique to substantially reduce the amount of material waste.

@unpublished{dawkins_terrain_2011,
	title = {Terrain {Characterization} and {Roughness} {Estimation} for {Simulation} and {Control} of {Unmanned} {Ground} {Vehicles}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/2912},
	abstract = {This dissertation presents a methodology for generating artificial terrains for simulation of off-road vehicles. Furthermore it develops and evaluates methods for characterizing the terrain for the control of unmanned ground vehicles. The terrain is the principle source of chassis excitation in off-road vehicles and the control of the vehicle is dependent on effectively characterizing the terrain slope, roughness, and surface condition. The previous work in this area is presented and the areas for improvement are identified. The literature is vast and is categorized into works which have addressed various parts of the problems. It is advantageous for the development of autonomous vehicle systems to simulate the vehicle response over various terrains; this requires generating artificial terrains which are similar to real terrains. Two methods for generating terrains based on the Weierstrass-Mandelbrot (W-M) fractal function are presented. The generated surfaces are evaluated using the root mean squared elevation (RMSE) and power spectral density (PSD). A seven degree of freedom (7-DOF) suspension model is developed for the purpose of evaluating the response of the vehicle on the generated terrains. The vehicle response is used to introduce motion based metrics for characterizing the roughness of the terrain. The root mean squared (RMS) vertical acceleration, RMS roll rate, and RMS pitch rate are introduced as potential motion base metrics. Additionally the phase plane of various vehicle states is investigated as a means for understanding the vehicle state combined with the terrain roughness. 
     A system for generating three dimensional point cloud maps of terrains is presented. Using a loosely coupled architecture Global Positioning System (GPS) and inertial navigation system (INS) are blended to provide estimates of the vehicle state. The system is implemented on the experimental vehicle to map various terrains. The terrain maps are characterized using RMSE, PSD, root mean squared slope (RMSS), and amplitude to wavelength ratio. Additionally, a feature extraction algorithm based on the wavelet transform is introduced. The response of the experimental vehicle on the terrains is analyzed using the RMS vertical acceleration, RMS roll rate, RMS pitch rate, and RMS suspension deflections. The 7-DOF suspension model of the experimental vehicle is then used to compare the simulated vehicle response to the experimental vehicle response. The model is then used to evaluate the effectiveness of the W-M function for generating artificial terrains. The response of the simulated vehicle on the experimental and generated terrains is then compared.
     It is determined that an artificial surface can be generated which will result in a similar vehicle response as the experimentally measured surface. The method does however have difficulty capturing the nuances of experimentally measured terrains. Additionally it is shown that the roughness of the terrain can be characterized by analyzing the surface with the RMSE, PSD, RMSS, or wavelength to amplitude ratio. The roughness can also be characterized by the RMS vertical acceleration, RMS roll rate, RMS pitch rate, or RMS suspension deflection. These methods are compared and their strengths and weaknesses are highlighted.},
	language = {en},
	urldate = {2024-06-25},
	author = {Dawkins, Jeremy},
	month = dec,
	year = {2011},
	note = {Accepted: 2011-12-02T13:57:26Z},
}

This dissertation presents a methodology for generating artificial terrains for simulation of off-road vehicles. Furthermore it develops and evaluates methods for characterizing the terrain for the control of unmanned ground vehicles. The terrain is the principle source of chassis excitation in off-road vehicles and the control of the vehicle is dependent on effectively characterizing the terrain slope, roughness, and surface condition. The previous work in this area is presented and the areas for improvement are identified. The literature is vast and is categorized into works which have addressed various parts of the problems. It is advantageous for the development of autonomous vehicle systems to simulate the vehicle response over various terrains; this requires generating artificial terrains which are similar to real terrains. Two methods for generating terrains based on the Weierstrass-Mandelbrot (W-M) fractal function are presented. The generated surfaces are evaluated using the root mean squared elevation (RMSE) and power spectral density (PSD). A seven degree of freedom (7-DOF) suspension model is developed for the purpose of evaluating the response of the vehicle on the generated terrains. The vehicle response is used to introduce motion based metrics for characterizing the roughness of the terrain. The root mean squared (RMS) vertical acceleration, RMS roll rate, and RMS pitch rate are introduced as potential motion base metrics. Additionally the phase plane of various vehicle states is investigated as a means for understanding the vehicle state combined with the terrain roughness. A system for generating three dimensional point cloud maps of terrains is presented. Using a loosely coupled architecture Global Positioning System (GPS) and inertial navigation system (INS) are blended to provide estimates of the vehicle state. The system is implemented on the experimental vehicle to map various terrains. The terrain maps are characterized using RMSE, PSD, root mean squared slope (RMSS), and amplitude to wavelength ratio. Additionally, a feature extraction algorithm based on the wavelet transform is introduced. The response of the experimental vehicle on the terrains is analyzed using the RMS vertical acceleration, RMS roll rate, RMS pitch rate, and RMS suspension deflections. The 7-DOF suspension model of the experimental vehicle is then used to compare the simulated vehicle response to the experimental vehicle response. The model is then used to evaluate the effectiveness of the W-M function for generating artificial terrains. The response of the simulated vehicle on the experimental and generated terrains is then compared. It is determined that an artificial surface can be generated which will result in a similar vehicle response as the experimentally measured surface. The method does however have difficulty capturing the nuances of experimentally measured terrains. Additionally it is shown that the roughness of the terrain can be characterized by analyzing the surface with the RMSE, PSD, RMSS, or wavelength to amplitude ratio. The roughness can also be characterized by the RMS vertical acceleration, RMS roll rate, RMS pitch rate, or RMS suspension deflection. These methods are compared and their strengths and weaknesses are highlighted.

@unpublished{krithivasan_theoretical_2011,
	title = {Theoretical and {Experimental} {Analysis} of {Strain} in a {Tire} {Under} {Static} {Loading} and {Steady}-{State} {Free}-{Rolling} {Conditions}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/2522},
	abstract = {This main objective of this work is to predict
the operating conditions or the state of a tire based on a
wireless sensor suit. First a three dimensional finite element
model of a standard reference test tire (SRTT) was developed to
better understand the tire deformation under separate cases
of static loading, steady state free-rolling and steady-state rolling conditions. A
parametric study of normal loading, slip angle and slip ratio was carried
out to capture the influence of these parameters. The numerical analysis techniques such as the Fouier analysis, 
Weibull curve fitting and slope curve method were explored to relate the tire strains to the various loads on the tire. The advantages and disadvantages of the various 
methods, mentioned above, for strain analysis is also presented. 

A wireless sensor suite comprising of analog devices (strain, pressure and temperature sensors)
was developed to capture the tire deformation under loading
conditions similar to those used in the finite element model.
This sensor suite formed the basis for experimentally verifying
the trends captured by the finite element model on a custom
built tire test stand with capabilities of mimicking real-time
conditions (under static loading scenario) of a tire in contact
with road and steady state conditions on a FlatTrac test bed.
Using the results from the experiments and the finite element
model an empirical model was developed which demonstrates how
the strains measured on the inner surface of the tire could be
used to quantify desired parameters such as slip angle, lateral
force, slip ratio, longitudinal force and normal load. This resulting empirical equations relate
measured strains to the normal load, slip angle, slip ratio, lateral force and longitudinal force.},
	language = {en},
	urldate = {2024-06-25},
	author = {Krithivasan, Vijaykumar},
	month = apr,
	year = {2011},
	note = {Accepted: 2011-04-11T20:02:52Z},
}

This main objective of this work is to predict the operating conditions or the state of a tire based on a wireless sensor suit. First a three dimensional finite element model of a standard reference test tire (SRTT) was developed to better understand the tire deformation under separate cases of static loading, steady state free-rolling and steady-state rolling conditions. A parametric study of normal loading, slip angle and slip ratio was carried out to capture the influence of these parameters. The numerical analysis techniques such as the Fouier analysis, Weibull curve fitting and slope curve method were explored to relate the tire strains to the various loads on the tire. The advantages and disadvantages of the various methods, mentioned above, for strain analysis is also presented. A wireless sensor suite comprising of analog devices (strain, pressure and temperature sensors) was developed to capture the tire deformation under loading conditions similar to those used in the finite element model. This sensor suite formed the basis for experimentally verifying the trends captured by the finite element model on a custom built tire test stand with capabilities of mimicking real-time conditions (under static loading scenario) of a tire in contact with road and steady state conditions on a FlatTrac test bed. Using the results from the experiments and the finite element model an empirical model was developed which demonstrates how the strains measured on the inner surface of the tire could be used to quantify desired parameters such as slip angle, lateral force, slip ratio, longitudinal force and normal load. This resulting empirical equations relate measured strains to the normal load, slip angle, slip ratio, lateral force and longitudinal force.

@inproceedings{broderick_simple_2011,
	title = {Simple {Calibration} for {Vehicle} {Pose} {Estimation} {Using} {Gaussian} {Processes}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=9488},
	abstract = {A method of estimating a vehicle's attitude in relation to the road surface using only light detection and ranging (LiDAR) measurements is presented. Gaussian processes, a machine learning technique, are used to relate the measurements of the road surface to the pitch and roll of the vehicle. Difficulties regarding sensor calibration are discussed and addressed successfully. The method and associated calibration of the LiDAR sensor are focused on allowing realtime calculation and simplifying calibration so that it can be performed in the field without any additional mechanisms or specialized targets. A method of determining the lever arm between the LiDAR and the center of gravity of the vehicle is developed and presented. On-vehicle results show that the attitude calculations are able to be implemented in a real-time system and have been compared against a multi-antenna GPS attitude measurement for accuracy.},
	language = {en},
	urldate = {2024-06-20},
	author = {Broderick, D. J. and Britt, J. and Ryan, J. and Bevly, D. M. and Hung, J. Y.},
	month = jan,
	year = {2011},
	pages = {447--458},
}

A method of estimating a vehicle's attitude in relation to the road surface using only light detection and ranging (LiDAR) measurements is presented. Gaussian processes, a machine learning technique, are used to relate the measurements of the road surface to the pitch and roll of the vehicle. Difficulties regarding sensor calibration are discussed and addressed successfully. The method and associated calibration of the LiDAR sensor are focused on allowing realtime calculation and simplifying calibration so that it can be performed in the field without any additional mechanisms or specialized targets. A method of determining the lever arm between the LiDAR and the center of gravity of the vehicle is developed and presented. On-vehicle results show that the attitude calculations are able to be implemented in a real-time system and have been compared against a multi-antenna GPS attitude measurement for accuracy.

@inproceedings{lashley_comparison_2011,
	title = {Comparison in the {Performance} of the {Vector} {Delay}/{Frequency} {Lock} {Loop} and {Equivalent} {Scalar} {Tracking} {Loops} in {Dense} {Foliage} and {Urban} {Canyon}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=9726},
	abstract = {The performance of the vector delay/frequency lock loop (VDFLL) is compared to that of the equivalent scalar tracking loops in environments with dense foliage and extreme urban canyon in this paper. The VDFLL and equivalent scalar tracking loops use the same coherent integration times, C/N0 ratio estimators, process noise tunings, and discriminators. The performance of the VDFLL is also compared to that of a high-end commercial GPS receiver. The VDFLL and equivalent scalar tracking loops maintain signal lock on all the available satellites in the areas with dense foliage. The VDFLL significantly outperforms the scalar tracking loops and the commercial GPS receiver in the urban canyon environment. Specific details on the implementation of the VDFLL are provided in the appendices. Index Terms—GPS; deep integration; ultra-tight coupling; vector tracking; vector delay lock loop; vector frequency lock loop;},
	language = {en},
	urldate = {2024-06-20},
	author = {Lashley, Matthew and Bevly, David M.},
	month = sep,
	year = {2011},
	pages = {1786--1803},
}

The performance of the vector delay/frequency lock loop (VDFLL) is compared to that of the equivalent scalar tracking loops in environments with dense foliage and extreme urban canyon in this paper. The VDFLL and equivalent scalar tracking loops use the same coherent integration times, C/N0 ratio estimators, process noise tunings, and discriminators. The performance of the VDFLL is also compared to that of a high-end commercial GPS receiver. The VDFLL and equivalent scalar tracking loops maintain signal lock on all the available satellites in the areas with dense foliage. The VDFLL significantly outperforms the scalar tracking loops and the commercial GPS receiver in the urban canyon environment. Specific details on the implementation of the VDFLL are provided in the appendices. Index Terms—GPS; deep integration; ultra-tight coupling; vector tracking; vector delay lock loop; vector frequency lock loop;

@inproceedings{britt_comparative_2011,
	title = {A {Comparative} {Study} of {Lidar} and {Camera}-based {Lane} {Departure} {Warning} {Systems}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=9593},
	abstract = {This paper presents a comparison of a lidar and camera based lane departure warning methods. The two methods are analyzed based on their ability to determine the position of the vehicle in the lane under various weather and lighting scenarios. The position of the vehicle reported by the vision systems is compared to a precision survey of the lane markings at the National Center for Asphalt Technology (NCAT) test track and an RTK position of the vehicle. The criteria used to assess the performance of the two methods are based on detection rates, position error, and position variance.},
	language = {en},
	urldate = {2024-06-20},
	author = {Britt, Jordan and Rose, Christopher and Bevly, David M.},
	month = sep,
	year = {2011},
	pages = {324--332},
}

This paper presents a comparison of a lidar and camera based lane departure warning methods. The two methods are analyzed based on their ability to determine the position of the vehicle in the lane under various weather and lighting scenarios. The position of the vehicle reported by the vision systems is compared to a precision survey of the lane markings at the National Center for Asphalt Technology (NCAT) test track and an RTK position of the vehicle. The criteria used to assess the performance of the two methods are based on detection rates, position error, and position variance.

@inproceedings{britt_dynamic_2011,
	title = {Dynamic {Testing} and {Calibration} of {Gaussian} {Processes} for {Vehicle} {Attitude} {Estimation}},
	volume = {1},
	url = {https://ieeexplore.ieee.org/document/6146955/;jsessionid=1E916697288B99715E42B50B23E2A5E4},
	doi = {10.1109/ICMLA.2011.61},
	abstract = {A method of estimating a vehicle's attitude in relation to the road surface using only light detection and ranging (lidar) measurements is presented. Gaussian processes, a machine learning technique, is used to relate the measurements of the road surface to the pitch and roll of the vehicle. Testing was performed under normal driving conditions on a test track as well as under high dynamic maneuvers on a skid-pad to assess performance of the algorithm. On-vehicle results show that the attitude calculations are capable of being implemented in a real-time system and have been compared against a multi-antenna GPS attitude measurement for accuracy.},
	urldate = {2024-06-20},
	booktitle = {2011 10th {International} {Conference} on {Machine} {Learning} and {Applications} and {Workshops}},
	author = {Britt, Jordan and Broderick, David J. and Bevly, David M. and Hung, John Y.},
	month = dec,
	year = {2011},
	keywords = {Estimation, Gaussian processes, Laser radar, Roads, Testing, Training, Training data, Vehicles, attitude, lidar},
	pages = {124--128},
}

A method of estimating a vehicle's attitude in relation to the road surface using only light detection and ranging (lidar) measurements is presented. Gaussian processes, a machine learning technique, is used to relate the measurements of the road surface to the pitch and roll of the vehicle. Testing was performed under normal driving conditions on a test track as well as under high dynamic maneuvers on a skid-pad to assess performance of the algorithm. On-vehicle results show that the attitude calculations are capable of being implemented in a real-time system and have been compared against a multi-antenna GPS attitude measurement for accuracy.

@article{britt_embedded_2011,
	title = {An embedded system for real-time navigation and remote command of a trained canine},
	volume = {15},
	issn = {1617-4917},
	url = {https://doi.org/10.1007/s00779-010-0298-4},
	doi = {10.1007/s00779-010-0298-4},
	abstract = {This paper demonstrates a capability to use a developed embedded sensor suite to consistently track the position, motion behavior, and orientation of a canine. Quantifying and recording canine position and motion in real time provides a useful mechanism for objective analysis of canine trials and missions. We provide a detailed description of the sensor equipment, including the global position satellite (GPS) receiver and antenna, accelerometers, gyroscopes, and magnetometers. Sensors beyond GPS provide for higher frequency readings, a tolerance to GPS loss, and the ability to characterize canine orientation. We demonstrate integrating sensor measurements using an Extended Kalman Filter (EKF) to estimate the canine position and velocity during temporary GPS loss. The system supports the remote actuation of tone and vibration commands and reports commands in real time alongside sensor data. This extends the range at which a handler could monitor a canine and allows enhanced trial analysis using raw sensor data and visualizations. To illustrate the system capabilities, we performed a case study in the remote command and navigation of a trained canine by a professional trainer. The results of this case study are analyzed in terms of canine trial success, motion behavior analysis, and in the context of simulated GPS losses. We discuss other potential applications of the system in autonomous canine command, canine motion analysis, and non-canine applications.},
	language = {en},
	number = {1},
	urldate = {2024-06-20},
	journal = {Personal and Ubiquitous Computing},
	author = {Britt, Winard R. and Miller, Jeffrey and Waggoner, Paul and Bevly, David M. and Hamilton, John A.},
	month = jan,
	year = {2011},
	keywords = {Canine augmentation technology, Canine guidance, Embedded systems, Sensor aggregation, Sensor navigation},
	pages = {61--74},
}

This paper demonstrates a capability to use a developed embedded sensor suite to consistently track the position, motion behavior, and orientation of a canine. Quantifying and recording canine position and motion in real time provides a useful mechanism for objective analysis of canine trials and missions. We provide a detailed description of the sensor equipment, including the global position satellite (GPS) receiver and antenna, accelerometers, gyroscopes, and magnetometers. Sensors beyond GPS provide for higher frequency readings, a tolerance to GPS loss, and the ability to characterize canine orientation. We demonstrate integrating sensor measurements using an Extended Kalman Filter (EKF) to estimate the canine position and velocity during temporary GPS loss. The system supports the remote actuation of tone and vibration commands and reports commands in real time alongside sensor data. This extends the range at which a handler could monitor a canine and allows enhanced trial analysis using raw sensor data and visualizations. To illustrate the system capabilities, we performed a case study in the remote command and navigation of a trained canine by a professional trainer. The results of this case study are analyzed in terms of canine trial success, motion behavior analysis, and in the context of simulated GPS losses. We discuss other potential applications of the system in autonomous canine command, canine motion analysis, and non-canine applications.

@article{travis_automated_2011,
	title = {Automated short distance vehicle following using a dynamic base {RTK} system},
	volume = {9},
	issn = {1471-0226, 1741-5306},
	url = {http://www.inderscience.com/link.php?id=38183},
	doi = {10.1504/IJVAS.2011.038183},
	language = {en},
	number = {1/2},
	urldate = {2024-06-20},
	journal = {International Journal of Vehicle Autonomous Systems},
	author = {Travis, William and Martin, Scott and Bevly, David M.},
	year = {2011},
	pages = {126},
}

@unpublished{rose_lane_2010,
	type = {thesis},
	title = {Lane {Level} {Localization} with {Camera} and {Inertial} {Measurement} {Unit} using an {Extended} {Kalman} {Filter}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/2420},
	abstract = {This thesis studies a technique for combining vision and inertial measurement unit (IMU) data to increase the reliability of lane departure warning systems.  In this technique, 2nd-order polynomials are used to model the likelihood area of the location of the lane marking position in the image as well as the lane itself.  An IMU is used to predict the drift of these polynomials and the estimated lane marking when the lane markings can not be detected in the image.  Subsequent frames where the lane marking is present results in faster convergence of the model on the lane marking due to a reduced number of detected erroneous lines.

A technique to reduce the effect of untracked lane markings has been employed which bounds the previously detected 2nd-order polynomial with two other polynomials within which lies the likelihood region of the next frame's lane marking.  Similarly, the slope at each point on the lane marking model lies within a certain range with respect to the previously detected 2nd-order polynomial.  These bounds and slope employ similar characteristics as the original line; therefore, the lane marking should be detected within the bounded area and within the expected slope range given smooth transitions between each frame.

An inertial measurement unit can provide accelerations and rotation rates of a vehicle.  Using an extended Kalman filter, information from the IMU can be blended with the last known coefficients of the estimated lane marking to approximate the lane marking coefficients until the lane is detected.  A measurement of the position within the lane can be carried out by determining the number of pixels from the center of the image and the estimated lane marking.  This measurement value can then be converted to its real-world equivalent and used to estimate the position of the vehicle within the lane.  Also, the heading of the vehicle can be determined by examining the distance from the vanishing point of the camera and the vanishing point of the lane markings.},
	language = {en},
	urldate = {2024-06-25},
	author = {Rose, Christopher},
	month = dec,
	year = {2010},
	note = {Accepted: 2010-12-07T19:16:20Z},
}

This thesis studies a technique for combining vision and inertial measurement unit (IMU) data to increase the reliability of lane departure warning systems. In this technique, 2nd-order polynomials are used to model the likelihood area of the location of the lane marking position in the image as well as the lane itself. An IMU is used to predict the drift of these polynomials and the estimated lane marking when the lane markings can not be detected in the image. Subsequent frames where the lane marking is present results in faster convergence of the model on the lane marking due to a reduced number of detected erroneous lines. A technique to reduce the effect of untracked lane markings has been employed which bounds the previously detected 2nd-order polynomial with two other polynomials within which lies the likelihood region of the next frame's lane marking. Similarly, the slope at each point on the lane marking model lies within a certain range with respect to the previously detected 2nd-order polynomial. These bounds and slope employ similar characteristics as the original line; therefore, the lane marking should be detected within the bounded area and within the expected slope range given smooth transitions between each frame. An inertial measurement unit can provide accelerations and rotation rates of a vehicle. Using an extended Kalman filter, information from the IMU can be blended with the last known coefficients of the estimated lane marking to approximate the lane marking coefficients until the lane is detected. A measurement of the position within the lane can be carried out by determining the number of pixels from the center of the image and the estimated lane marking. This measurement value can then be converted to its real-world equivalent and used to estimate the position of the vehicle within the lane. Also, the heading of the vehicle can be determined by examining the distance from the vanishing point of the camera and the vanishing point of the lane markings.

@unpublished{edwards_development_2010,
	type = {thesis},
	title = {Development of a {GPS} {Software} {Receiver} on an {FPGA} for {Testing} {Advanced} {Tracking} {Algorithms}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/2239},
	abstract = {In this thesis, the development of an FPGA-based software GPS receiver with a special focus on advanced tracking algorithms is developed. The particular algorithms of note in this thesis are in a class known as vector tracking algorithms. Vector tracking GPS algorithms boast an increased immunity to interference and jamming and the ability to perform at low signal-to-noise ratios. Addition of an inertial device to the vector tracking algorithm is known as deep integration and further boosts these benefits. A trade study is presented that compares different hardware platforms for an embedded real-time system. An FPGA is chosen based on its ability to combine all of the necessary functions on a single device and its ability to seque a FPGA logic design to an application-specific integrated circuit (ASIC). Implementation details of each different component that constitutes a GPS receiver are given. In the single system, three soft-core microprocessors are synthesized on the FPGA to compute various components of the GPS algorithm, and their interfacing to other custom logic and to each other is described. The operation of each of the custom GPS logic modules is outlined in detail. Hardware resource utilization and computational timing results are also given. This thesis shows that a preliminary design of a real-time embedded GPS receiver capable of vector tracking is feasible, but there are more improvements to be made before deep integration is successful in real time.},
	language = {en},
	urldate = {2024-06-25},
	author = {Edwards, William Luke},
	month = jul,
	year = {2010},
	note = {Accepted: 2010-07-20T21:22:46Z},
}

In this thesis, the development of an FPGA-based software GPS receiver with a special focus on advanced tracking algorithms is developed. The particular algorithms of note in this thesis are in a class known as vector tracking algorithms. Vector tracking GPS algorithms boast an increased immunity to interference and jamming and the ability to perform at low signal-to-noise ratios. Addition of an inertial device to the vector tracking algorithm is known as deep integration and further boosts these benefits. A trade study is presented that compares different hardware platforms for an embedded real-time system. An FPGA is chosen based on its ability to combine all of the necessary functions on a single device and its ability to seque a FPGA logic design to an application-specific integrated circuit (ASIC). Implementation details of each different component that constitutes a GPS receiver are given. In the single system, three soft-core microprocessors are synthesized on the FPGA to compute various components of the GPS algorithm, and their interfacing to other custom logic and to each other is described. The operation of each of the custom GPS logic modules is outlined in detail. Hardware resource utilization and computational timing results are also given. This thesis shows that a preliminary design of a real-time embedded GPS receiver capable of vector tracking is feasible, but there are more improvements to be made before deep integration is successful in real time.

@unpublished{britt_lane_2010,
	type = {thesis},
	title = {Lane {Detection}, {Calibration}, and {Attitude} {Determination} with a {Multi}-{Layer} {Lidar} for {Vehicle} {Safety} {Systems}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/2366},
	abstract = {This thesis develops a lane detection algorithm which extracts lane markings from the road's surface in an effort to ascertain the lateral position of the vehicle in the lane using a lidar, with the goal of being incorporated into a larger lane departure warning system. The presented algorithm underwent numerous highway tests. These tests include both a comparison of the reported position of the algorithm using the lidar to a high accuracy global positioning system (GPS) as well tests more commonly found in literature. The results of which show that the presented algorithm is capable of determining its position in the lane to a high degree of accuracy and consistency.

Abstract Additionally, a novel lidar calibration method is developed which is capable of calibrating a 3D forward facing lidar mounted on a vehicle to a plane, through simply causing the vehicle to pitch. The presented algorithm will demonstrate the ability to determine vehicle attitude with sub degree accuracy. The algorithm is tested under a number of conditions ranging from in lab tests to on vehicle tests. During these test both attitude accuracy as well as processing time are analyzed. Finally, it is shown that this algorithm is capable of making highly accurate attitude calculations at a rate that is capable of running real-time.},
	language = {en},
	urldate = {2024-06-25},
	author = {Britt, Jordan},
	month = nov,
	year = {2010},
	note = {Accepted: 2010-11-05T19:10:43Z},
}

This thesis develops a lane detection algorithm which extracts lane markings from the road's surface in an effort to ascertain the lateral position of the vehicle in the lane using a lidar, with the goal of being incorporated into a larger lane departure warning system. The presented algorithm underwent numerous highway tests. These tests include both a comparison of the reported position of the algorithm using the lidar to a high accuracy global positioning system (GPS) as well tests more commonly found in literature. The results of which show that the presented algorithm is capable of determining its position in the lane to a high degree of accuracy and consistency. Abstract Additionally, a novel lidar calibration method is developed which is capable of calibrating a 3D forward facing lidar mounted on a vehicle to a plane, through simply causing the vehicle to pitch. The presented algorithm will demonstrate the ability to determine vehicle attitude with sub degree accuracy. The algorithm is tested under a number of conditions ranging from in lab tests to on vehicle tests. During these test both attitude accuracy as well as processing time are analyzed. Finally, it is shown that this algorithm is capable of making highly accurate attitude calculations at a rate that is capable of running real-time.

@unpublished{miller_maximum_2010,
	title = {A {Maximum} {Effort} {Control} {System} for the {Tracking} and {Control} of a {Guided} {Canine}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/2400},
	abstract = {This dissertation presents an approach for autonomously controlling a canine using an embedded command module with vibration and tone generation capabilities and an embedded control suite comprised of a microprocessor, wireless radio, GPS receiver, three accelerometers, three gyroscopes, and three magnetometers. In order to track the canine’s motions, which inherently contain non-conventional noise characteristics, GPS, inertial sensor, and magnetometer measurements were integrated using a specialized Extended Kalman Filter (EKF), equipped with a Fuzzy Logic Controller for adaptive tuning of the Process Noise Covariance Matrix (Q). This allowed for rejection of unmodeled canine motion characteristics which tend to corrupt accelerometer bias tracking in a standard EKF. The EKF solution provided an optimized estimate of the canine position and velocity and also proved to be effective in tracking the canine’s position and velocity during brief GPS outages. On average, the filter proved to track the canine’s position with a 7.5 meter error and the canine’s velocity with a 1.2 meter per second error after 10 seconds of simulated GPS outage.
Using the tracking solution, a Canine Maximum Effort Controller (CMEC) was implemented for autonomous control of the canine. The CMEC proved to be effective at guiding the canine to multiple waypoints. Results from structured and non-structured environment two waypoint trials indicated a 97.7\% success rate. Three waypoint trials resulted in a success rate of 70.1\%, and the overall success rate of the control system was found to be 86.6\%.
In order to determine the best orientation deviation threshold choice to be used in the CMEC in future work without resorting to trial and error, a Canine Trial Simulator (CTS) was developed based on a Canine Behavior Statistical Model (CBSM) and the CMEC. The CBSM was comprised of actual statistical information that describes a canine’s behavior over time. After simulations of two and three waypoint trials and verification with previously conducted field trials, it was determined that for the canine used in this dissertation, an orientation deviation threshold between 40 and 50 degrees would be ideal for use in the CMEC.},
	language = {en},
	urldate = {2024-06-25},
	author = {Miller, Jeffrey David},
	month = dec,
	year = {2010},
	note = {Accepted: 2010-12-02T17:31:36Z},
}

This dissertation presents an approach for autonomously controlling a canine using an embedded command module with vibration and tone generation capabilities and an embedded control suite comprised of a microprocessor, wireless radio, GPS receiver, three accelerometers, three gyroscopes, and three magnetometers. In order to track the canine’s motions, which inherently contain non-conventional noise characteristics, GPS, inertial sensor, and magnetometer measurements were integrated using a specialized Extended Kalman Filter (EKF), equipped with a Fuzzy Logic Controller for adaptive tuning of the Process Noise Covariance Matrix (Q). This allowed for rejection of unmodeled canine motion characteristics which tend to corrupt accelerometer bias tracking in a standard EKF. The EKF solution provided an optimized estimate of the canine position and velocity and also proved to be effective in tracking the canine’s position and velocity during brief GPS outages. On average, the filter proved to track the canine’s position with a 7.5 meter error and the canine’s velocity with a 1.2 meter per second error after 10 seconds of simulated GPS outage. Using the tracking solution, a Canine Maximum Effort Controller (CMEC) was implemented for autonomous control of the canine. The CMEC proved to be effective at guiding the canine to multiple waypoints. Results from structured and non-structured environment two waypoint trials indicated a 97.7% success rate. Three waypoint trials resulted in a success rate of 70.1%, and the overall success rate of the control system was found to be 86.6%. In order to determine the best orientation deviation threshold choice to be used in the CMEC in future work without resorting to trial and error, a Canine Trial Simulator (CTS) was developed based on a Canine Behavior Statistical Model (CBSM) and the CMEC. The CBSM was comprised of actual statistical information that describes a canine’s behavior over time. After simulations of two and three waypoint trials and verification with previously conducted field trials, it was determined that for the canine used in this dissertation, an orientation deviation threshold between 40 and 50 degrees would be ideal for use in the CMEC.

@unpublished{huang_design_2010,
	title = {Design and {Evaluation} of a {3D} {Road} {Geometry} {Based} {Heavy} {Truck} {Fuel} {Optimization} {System}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/2252},
	abstract = {This dissertation develops a 3D road geometry based optimal powertrain control system in reducing the fuel consumption of heavy trucks. The real-time optimal control (OC) system, solving a constrained nonlinear programming problem, is designed to predict and command the optimal throttle, brake torque (generated from the engine retarder), gear
shifting, and velocity trajectory to minimize the fuel consumption and travel time. Throttle and gear shifting are continuous and discrete control inputs respectively, which is a mixeddiscrete nonlinear programming problem (MDNLP). The optimization solver developed is
an interior-point algorithm plus a rounding-off method, where all discrete gear ratios are handled as continuous variables and optimized, and then the optimal discrete gear ratios are
obtained by rounding up each continuous gear ratio to the nearest discrete value.
Simulation and experimental tests of a Class 8 truck are conducted with GIS 3D road geometries. Test results show that the optimal control system is able to reduce fuel consumption up to 3.0\% with small travel time increases on level and rolling terrains when compared to the defined baseline. When on the highly mountainous terrain with steep crest slope and
long slope length, the OC could only save a small amount of fuel. Thus, it is found that the gain in fuel economy is directly effected by the change in terrain type.
Additionally, sensitivity analyses for the terrain and road geometry are conducted to investigate how the change of the terrain and the errors in the terrain data effect the gain in fuel economy and the system performance. For the terrain sensitivity, it is found that the gain in fuel economy is directly related to the change of road grade (both the magnitude and
frequency) and slope length. For the terrain error sensitivity, the road error largely effects
both the fuel economy and the system performance. This research reveals that the impact from the absolute error (a shift in the slope position) on the fuel savings is not as evident as that from the relative error (a different slope value). The impact from both absolute and relative errors on the system performance is significant, which shows the requirement to apply a high accuracy road map in real road tests as well as in production uses.},
	language = {en},
	urldate = {2024-06-25},
	author = {Huang, Wei},
	month = jul,
	year = {2010},
	note = {Accepted: 2010-07-28T17:58:37Z},
}

This dissertation develops a 3D road geometry based optimal powertrain control system in reducing the fuel consumption of heavy trucks. The real-time optimal control (OC) system, solving a constrained nonlinear programming problem, is designed to predict and command the optimal throttle, brake torque (generated from the engine retarder), gear shifting, and velocity trajectory to minimize the fuel consumption and travel time. Throttle and gear shifting are continuous and discrete control inputs respectively, which is a mixeddiscrete nonlinear programming problem (MDNLP). The optimization solver developed is an interior-point algorithm plus a rounding-off method, where all discrete gear ratios are handled as continuous variables and optimized, and then the optimal discrete gear ratios are obtained by rounding up each continuous gear ratio to the nearest discrete value. Simulation and experimental tests of a Class 8 truck are conducted with GIS 3D road geometries. Test results show that the optimal control system is able to reduce fuel consumption up to 3.0% with small travel time increases on level and rolling terrains when compared to the defined baseline. When on the highly mountainous terrain with steep crest slope and long slope length, the OC could only save a small amount of fuel. Thus, it is found that the gain in fuel economy is directly effected by the change in terrain type. Additionally, sensitivity analyses for the terrain and road geometry are conducted to investigate how the change of the terrain and the errors in the terrain data effect the gain in fuel economy and the system performance. For the terrain sensitivity, it is found that the gain in fuel economy is directly related to the change of road grade (both the magnitude and frequency) and slope length. For the terrain error sensitivity, the road error largely effects both the fuel economy and the system performance. This research reveals that the impact from the absolute error (a shift in the slope position) on the fuel savings is not as evident as that from the relative error (a different slope value). The impact from both absolute and relative errors on the system performance is significant, which shows the requirement to apply a high accuracy road map in real road tests as well as in production uses.

@unpublished{travis_path_2010,
	title = {Path {Duplication} {Using} {GPS} {Carrier} {Based} {Relative} {Position} for {Automated} {Ground} {Vehicle} {Convoys}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/2109},
	abstract = {A GPS based automated convoy strategy to duplicate the path of a lead vehicle is presented in this dissertation. Laser scanners and cameras are not used; all information available comes from GPS or inertial systems. An algorithm is detailed that uses GPS carrier phase measurements to determine relative position between two moving ground vehicles. Error analysis shows the accuracy is centimeter level. It is shown that the time to the first solution fix is dependent upon initial relative position accuracy, and that near instantaneous fixes can be realized if that accuracy is less than 20 centimeters. The relative positioning algorithm is then augmented with inertial measurement units to dead reckon through brief outages. Performance analysis of automotive and tactical grade units shows the twenty centimeter threshold can be maintained for only a few seconds with the automotive grade unit and for 14 seconds with the tactical unit.
Next, techniques to determine odometry information in vector form are discussed. Three methods are outlined: dead reckoning of inertial sensors, time differencing GPS carrier measurements to determine change in platform position, and aiding the time differenced carrier measurements with inertial measurements. Partial integration of a tactical grade inertial measurement unit provided the lowest error drift for the scenarios investigated, but the time differenced carrier phase approach provided the most cost feasible approach with similar accuracy. Finally, the relative position and odometry algorithms are used to generate a reference by which an automated following vehicle can replicate a lead vehicle's path of travel. The first method presented uses only the relative position information to determine a relative angle to the leader. Using the relative angle as a heading reference for a steering control causes the follower to drive at the lead vehicle, thereby creating a towing effect on the follower when both vehicles are in motion. Effective use of this method is limited to short following distances, or line of sight operation, similar to vision based following approaches. The following vehicle turns about a smaller radius than the lead vehicle, and this effect intensifies as following distance increases.
The second path duplication method allows for non line of sight operation by combining the vector odometry with the relative position to create a virtual leader to follow. The actual difference between the vehicles could be in excess of 100 meters, but the perceived distance is reduced to a predetermined value based on vehicle speed by re-generating the lead vehicle's position at a previous instance in time with the relative position and odometry information. Performance curves of path duplication accuracy versus following distance using different odometry techniques show that the partially integrated tactical unit provides the best performance, but the time differenced carrier approach offered very similar performance for a lower total system cost.
Both following methods were implemented on an unmanned ground vehicle. Tests showed following accuracy for the line of sight method was within 50 centimeters on straight sections, though the reference accuracy was centimeter level. The non line of sight method predicted the virtual leader position to within 5 centimeters for following distances ranging from 10 to 120 meters.},
	language = {en},
	urldate = {2024-06-25},
	author = {Travis, William},
	month = apr,
	year = {2010},
	note = {Accepted: 2010-04-15T16:38:38Z},
}

A GPS based automated convoy strategy to duplicate the path of a lead vehicle is presented in this dissertation. Laser scanners and cameras are not used; all information available comes from GPS or inertial systems. An algorithm is detailed that uses GPS carrier phase measurements to determine relative position between two moving ground vehicles. Error analysis shows the accuracy is centimeter level. It is shown that the time to the first solution fix is dependent upon initial relative position accuracy, and that near instantaneous fixes can be realized if that accuracy is less than 20 centimeters. The relative positioning algorithm is then augmented with inertial measurement units to dead reckon through brief outages. Performance analysis of automotive and tactical grade units shows the twenty centimeter threshold can be maintained for only a few seconds with the automotive grade unit and for 14 seconds with the tactical unit. Next, techniques to determine odometry information in vector form are discussed. Three methods are outlined: dead reckoning of inertial sensors, time differencing GPS carrier measurements to determine change in platform position, and aiding the time differenced carrier measurements with inertial measurements. Partial integration of a tactical grade inertial measurement unit provided the lowest error drift for the scenarios investigated, but the time differenced carrier phase approach provided the most cost feasible approach with similar accuracy. Finally, the relative position and odometry algorithms are used to generate a reference by which an automated following vehicle can replicate a lead vehicle's path of travel. The first method presented uses only the relative position information to determine a relative angle to the leader. Using the relative angle as a heading reference for a steering control causes the follower to drive at the lead vehicle, thereby creating a towing effect on the follower when both vehicles are in motion. Effective use of this method is limited to short following distances, or line of sight operation, similar to vision based following approaches. The following vehicle turns about a smaller radius than the lead vehicle, and this effect intensifies as following distance increases. The second path duplication method allows for non line of sight operation by combining the vector odometry with the relative position to create a virtual leader to follow. The actual difference between the vehicles could be in excess of 100 meters, but the perceived distance is reduced to a predetermined value based on vehicle speed by re-generating the lead vehicle's position at a previous instance in time with the relative position and odometry information. Performance curves of path duplication accuracy versus following distance using different odometry techniques show that the partially integrated tactical unit provides the best performance, but the time differenced carrier approach offered very similar performance for a lower total system cost. Both following methods were implemented on an unmanned ground vehicle. Tests showed following accuracy for the line of sight method was within 50 centimeters on straight sections, though the reference accuracy was centimeter level. The non line of sight method predicted the virtual leader position to within 5 centimeters for following distances ranging from 10 to 120 meters.

@inproceedings{edwards_implementation_2010,
	title = {Implementation details of a deeply integrated {GPS}/{INS} software receiver},
	url = {https://ieeexplore.ieee.org/document/5507232/;jsessionid=4CDFCDE83ED3A14857D1797A39A80365},
	doi = {10.1109/PLANS.2010.5507232},
	abstract = {The goal of this paper is to describe the implementation details of an embedded GPS/INS software receiver. Several different methods of improving performance in difficult environments have been studied for the past few decades, but vector tracking and deep integration (or ultra-tight coupling) has been especially popular in the past few years. Vector tracking algorithms boast the ability to maintain signal lock in weak signal-to-noise ratio environments such as urban canyons or heavy foliage. Another touted benefit is the ability to instantly reacquire GPS signal lock after an outage. The addition of an inertial sensor to aid the vector tracking algorithms is known as deep integration or ultra-tight coupling. The addition of this inertial sensor further boosts immunity to jamming and receiver dynamics. Implementing vector tracking and deep integration on a real-time platform does not come without its drawbacks. Besides the typical real-time deadlines, a full traditional (non-vector) GPS receiver must be implemented to initialize the vector tracking algorithm. The addition of an IMU also requires the algorithm to track attitude and inertial bias states, which increases the size and complexity of the algorithm. In this paper, the design of an FPGA hardware platform to perform both traditional and vector tracking/deep integration is described in detail along with some preliminary computational results.},
	urldate = {2024-06-20},
	booktitle = {{IEEE}/{ION} {Position}, {Location} and {Navigation} {Symposium}},
	author = {Edwards, W. Luke and Clark, Benjamin J. and Bevly, David M.},
	month = may,
	year = {2010},
	note = {ISSN: 2153-3598},
	keywords = {Embedded software, FPGA, Field programmable gate arrays, GPS, Global Positioning System, Hardware, IMU, INS, Jamming, Navigation, Signal to noise ratio, State estimation, Tracking loops, Vehicle dynamics, deep integration, embedded, software receiver, ultra tight, vector tracking},
	pages = {1137--1146},
}

The goal of this paper is to describe the implementation details of an embedded GPS/INS software receiver. Several different methods of improving performance in difficult environments have been studied for the past few decades, but vector tracking and deep integration (or ultra-tight coupling) has been especially popular in the past few years. Vector tracking algorithms boast the ability to maintain signal lock in weak signal-to-noise ratio environments such as urban canyons or heavy foliage. Another touted benefit is the ability to instantly reacquire GPS signal lock after an outage. The addition of an inertial sensor to aid the vector tracking algorithms is known as deep integration or ultra-tight coupling. The addition of this inertial sensor further boosts immunity to jamming and receiver dynamics. Implementing vector tracking and deep integration on a real-time platform does not come without its drawbacks. Besides the typical real-time deadlines, a full traditional (non-vector) GPS receiver must be implemented to initialize the vector tracking algorithm. The addition of an IMU also requires the algorithm to track attitude and inertial bias states, which increases the size and complexity of the algorithm. In this paper, the design of an FPGA hardware platform to perform both traditional and vector tracking/deep integration is described in detail along with some preliminary computational results.

@inproceedings{lashley_analysis_2010,
	title = {Analysis of deeply integrated and tightly coupled architectures},
	url = {https://ieeexplore.ieee.org/document/5507127/;jsessionid=17BBE6515A9DF44D00DFD1CC7959BF70},
	doi = {10.1109/PLANS.2010.5507127},
	abstract = {This paper analyzes the impact that architectural features have on the performance of deeply integrated and tightly coupled algorithms. The effects of two specific architectural features are investigated. The first is the design of the Kalman filter used in the algorithms. The performance degradation caused by using a federated filtering architecture instead of a single, centralized filter is analyzed. The second feature is the usage of scalar and vector tracking loops. The advantage offered by vector tracking loops over scalar tracking loops is quantified. The effects of these two architectural features are determined by analyzing the comparative performance of three different algorithms. One algorithm uses a single Kalman filter to process the GPS signals and the inertial sensor data. The other two algorithms use a federated filtering architecture. One federated algorithm uses scalar tracking loops and the other uses vector tracking loops. Comparing the performance of the three algorithms allows the effects of filter design and tracking loop operation to be isolated. Covariance analysis and Monte Carlo simulations are used to study the performance of the algorithms with different inertial sensor grades and satellite constellations. The analysis reveals that the federated algorithm with vector tracking and the centralized filtering algorithm perform virtually identically. The federated algorithm with scalar tracking loops performs poorer. However, the performance of all three algorithms converge as the carrier to noise power density ratio declines. At low signal powers, all three algorithms provide identical performance. The results quantify how the architectural features of coupled systems affect their performance.},
	urldate = {2024-06-20},
	booktitle = {{IEEE}/{ION} {Position}, {Location} and {Navigation} {Symposium}},
	author = {Lashley, Matthew and Bevly, David M. and Hung, John Y.},
	month = may,
	year = {2010},
	note = {ISSN: 2153-3598},
	keywords = {Algorithm design and analysis, Degradation, Filtering algorithms, Filters, GPS, Global Positioning System, Performance analysis, Satellite constellations, Signal processing, Signal to noise ratio, Tracking loops, deep integration, tight coupling, ultra-tight coupling, vector delay lock loop, vector frequency lock loop, vector tracking},
	pages = {382--396},
}

This paper analyzes the impact that architectural features have on the performance of deeply integrated and tightly coupled algorithms. The effects of two specific architectural features are investigated. The first is the design of the Kalman filter used in the algorithms. The performance degradation caused by using a federated filtering architecture instead of a single, centralized filter is analyzed. The second feature is the usage of scalar and vector tracking loops. The advantage offered by vector tracking loops over scalar tracking loops is quantified. The effects of these two architectural features are determined by analyzing the comparative performance of three different algorithms. One algorithm uses a single Kalman filter to process the GPS signals and the inertial sensor data. The other two algorithms use a federated filtering architecture. One federated algorithm uses scalar tracking loops and the other uses vector tracking loops. Comparing the performance of the three algorithms allows the effects of filter design and tracking loop operation to be isolated. Covariance analysis and Monte Carlo simulations are used to study the performance of the algorithms with different inertial sensor grades and satellite constellations. The analysis reveals that the federated algorithm with vector tracking and the centralized filtering algorithm perform virtually identically. The federated algorithm with scalar tracking loops performs poorer. However, the performance of all three algorithms converge as the carrier to noise power density ratio declines. At low signal powers, all three algorithms provide identical performance. The results quantify how the architectural features of coupled systems affect their performance.

@inproceedings{giger_position_2010,
	title = {Position domain joint tracking},
	url = {https://ieeexplore.ieee.org/abstract/document/5707997},
	doi = {10.1109/NAVITEC.2010.5707997},
	abstract = {It was shown that the Vector Delay Lock Loop (VDLL) enhances the robustness of a GNSS receiver by exploiting the spatial correlation of the received signals. But due to the periodicity of the carrier, the VDLL only operates on the codephase and the carrier-frequency. In contrast to the VDLL, the Joint Tracking receiver manages to sustain the carrier-phase lock even in fast-changing, difficult environments. Other than the VDLL, the Joint Tracking algorithm doesn't estimate the receiver's location. The novel Position Domain Joint Tracking algorithm, described in this paper, combines both approaches, gaining from the advantages of both concepts. It is tested with signals generated by a constellation simulator, simulating a stationary and dynamic receiver. The test runs are discussed in terms of positioning performance. They show the big potential of such a combined receiver scheme as the signal synchronization is robust and the position estimate precise.},
	urldate = {2024-06-20},
	booktitle = {2010 5th {ESA} {Workshop} on {Satellite} {Navigation} {Technologies} and {European} {Workshop} on {GNSS} {Signals} and {Signal} {Processing} ({NAVITEC})},
	author = {Giger, Kaspar and Gu¨nther, Christoph},
	month = dec,
	year = {2010},
	note = {ISSN: 2325-5455},
	keywords = {Correlation, Joints, Noise, Receivers, Satellites, Synchronization, Tracking loops},
	pages = {1--8},
}

It was shown that the Vector Delay Lock Loop (VDLL) enhances the robustness of a GNSS receiver by exploiting the spatial correlation of the received signals. But due to the periodicity of the carrier, the VDLL only operates on the codephase and the carrier-frequency. In contrast to the VDLL, the Joint Tracking receiver manages to sustain the carrier-phase lock even in fast-changing, difficult environments. Other than the VDLL, the Joint Tracking algorithm doesn't estimate the receiver's location. The novel Position Domain Joint Tracking algorithm, described in this paper, combines both approaches, gaining from the advantages of both concepts. It is tested with signals generated by a constellation simulator, simulating a stationary and dynamic receiver. The test runs are discussed in terms of positioning performance. They show the big potential of such a combined receiver scheme as the signal synchronization is robust and the position estimate precise.

@inproceedings{lashley_valid_2010,
	title = {A valid comparison of vector and scalar tracking loops},
	url = {https://ieeexplore.ieee.org/document/5507215/;jsessionid=EF78C0E9F47B01D915A3AE0D4E596687},
	doi = {10.1109/PLANS.2010.5507215},
	abstract = {This paper analyzes the benefits offered by vector tracking loops relative to scalar tracking loops. A method for designing equivalent scalar and vector tracking loops is first introduced. The benefits of vector tracking are then determined by comparing the two equivalent algorithms. The improvements in signal tracking afforded by vector tracking are quantified in different scenarios using covariance analysis and Monte Carlo simulations. The vector tracking algorithms show a maximum improvement in tracking threshold of 6.2 dB with an eleven satellite constellation and a minimum improvement of 2.4 dB with a five satellite constellation. The results presented in this paper demonstrate the amount of improvement vector tracking can provide in different situations. Furthermore, the analysis technique used to design the equivalent tracking loops provides a simple way to compare other attributes of the algorithms, such as their multipath immunity and robustness.},
	urldate = {2024-06-20},
	booktitle = {{IEEE}/{ION} {Position}, {Location} and {Navigation} {Symposium}},
	author = {Lashley, Matthew and Bevly, David M. and Hung, John Y.},
	month = may,
	year = {2010},
	note = {ISSN: 2153-3598},
	keywords = {Algorithm design and analysis, Design methodology, Frequency locked loops, GPS, Global Positioning System, Mechanical engineering, Navigation, Paper technology, Satellite constellations, Signal processing, Tracking loops, deep integration, ultra-tight coupling, vector delay lock loop, vector frequency lock loop, vector tracking},
	pages = {464--474},
}

This paper analyzes the benefits offered by vector tracking loops relative to scalar tracking loops. A method for designing equivalent scalar and vector tracking loops is first introduced. The benefits of vector tracking are then determined by comparing the two equivalent algorithms. The improvements in signal tracking afforded by vector tracking are quantified in different scenarios using covariance analysis and Monte Carlo simulations. The vector tracking algorithms show a maximum improvement in tracking threshold of 6.2 dB with an eleven satellite constellation and a minimum improvement of 2.4 dB with a five satellite constellation. The results presented in this paper demonstrate the amount of improvement vector tracking can provide in different situations. Furthermore, the analysis technique used to design the equivalent tracking loops provides a simple way to compare other attributes of the algorithms, such as their multipath immunity and robustness.

@inproceedings{martin_performance_2010,
	title = {Performance comparison of single and dual frequency closely coupled {GPS}/{INS} relative positioning systems},
	url = {https://ieeexplore.ieee.org/document/5507307/;jsessionid=A457B53073616D615FFB8A3F5EDBD9B8},
	doi = {10.1109/PLANS.2010.5507307},
	abstract = {Single and dual frequency closely coupled GPS/INS relative positioning systems have been developed for use in automated ground vehicle convoys. The accuracy of the GPS carrier phase measurement is exploited to produce a high precision relative position vector between vehicles. The inertial systems of the lead vehicle and following vehicle are aligned using closely coupled GPS/INS filters on each vehicle and are used to output a high rate solution. Previous comparative studies focus on relative positioning with a fixed base station or are proprietary studies with limited discloser. The relative navigation solution presented here is referenced to a moving base station. Moving base stations in relative navigation problems have been addressed previously for airborne systems including automated air refueling and ship board landing systems. However, automated ground vehicles offer unique challenges due to the operational environment. Multipath, signal blockage, and cycle slip are more prevalent in ground applications. Testing was performed offline using data collected from two vehicles operating in various environments. Performance was evaluated based on accuracy, time to integer ambiguity reacquisition after a GPS outage and robustness of the navigation solution to faulty measurements. Pseudorange measurements are corrupted with additive noise to evaluate fault detection capabilities.},
	urldate = {2024-06-20},
	booktitle = {{IEEE}/{ION} {Position}, {Location} and {Navigation} {Symposium}},
	author = {Martin, Scott and Travis, William and Bevly, David},
	month = may,
	year = {2010},
	note = {ISSN: 2153-3598},
	keywords = {Base stations, DGPS, Frequency, Global Positioning System, Land vehicles, Navigation, Phase measurement, Remotely operated vehicles, Satellites, Vehicle driving, Vehicle dynamics, autonomous convoys, relative navigation},
	pages = {544--551},
}

Single and dual frequency closely coupled GPS/INS relative positioning systems have been developed for use in automated ground vehicle convoys. The accuracy of the GPS carrier phase measurement is exploited to produce a high precision relative position vector between vehicles. The inertial systems of the lead vehicle and following vehicle are aligned using closely coupled GPS/INS filters on each vehicle and are used to output a high rate solution. Previous comparative studies focus on relative positioning with a fixed base station or are proprietary studies with limited discloser. The relative navigation solution presented here is referenced to a moving base station. Moving base stations in relative navigation problems have been addressed previously for airborne systems including automated air refueling and ship board landing systems. However, automated ground vehicles offer unique challenges due to the operational environment. Multipath, signal blockage, and cycle slip are more prevalent in ground applications. Testing was performed offline using data collected from two vehicles operating in various environments. Performance was evaluated based on accuracy, time to integer ambiguity reacquisition after a GPS outage and robustness of the navigation solution to faulty measurements. Pseudorange measurements are corrupted with additive noise to evaluate fault detection capabilities.

@inproceedings{ryan_state_2010,
	address = {Cambridge, Massachusetts, USA},
	title = {State {Estimation} for {Vehicle} {Stability} {Control}: {A} {Kinematic} {Approach} {Using} {Only} {GPS} and {VSC} {Sensors}},
	isbn = {978-0-7918-4418-2},
	shorttitle = {State {Estimation} for {Vehicle} {Stability} {Control}},
	url = {https://asmedigitalcollection.asme.org/DSCC/proceedings/DSCC2010/44182/773/348772},
	doi = {10.1115/DSCC2010-4162},
	abstract = {It is well known that the vehicle sideslip and roll angles are very important for vehicle stability control systems. There has been much work focusing on estimating these states, however much of this work assumes knowledge of vehicle parameters or requires sensors which are currently not available on passenger vehicles for cost reasons. This paper presents a method of applying GPS/INS integration strategies to this particular estimation problem. Using a single antenna GPS receiver with a reduced set of INS sensors common to vehicle stability control systems, estimates of the roll and sideslip angles which are robust to different road geometries and changing vehicle parameters can be achieved. While the future may afford the luxury of using more sensors of higher quality, this work offers results which are applicable in today’s market and which would also serve as a means of redundancy in the future.},
	urldate = {2024-06-20},
	booktitle = {{ASME} 2010 {Dynamic} {Systems} and {Control} {Conference}, {Volume} 2},
	publisher = {ASMEDC},
	author = {Ryan, Jonathan and Lu, Jianbo and Bevly, David},
	month = jan,
	year = {2010},
	pages = {773--780},
}

It is well known that the vehicle sideslip and roll angles are very important for vehicle stability control systems. There has been much work focusing on estimating these states, however much of this work assumes knowledge of vehicle parameters or requires sensors which are currently not available on passenger vehicles for cost reasons. This paper presents a method of applying GPS/INS integration strategies to this particular estimation problem. Using a single antenna GPS receiver with a reduced set of INS sensors common to vehicle stability control systems, estimates of the roll and sideslip angles which are robust to different road geometries and changing vehicle parameters can be achieved. While the future may afford the luxury of using more sensors of higher quality, this work offers results which are applicable in today’s market and which would also serve as a means of redundancy in the future.

@inproceedings{brown_road_2010,
	address = {Cambridge, Massachusetts, USA},
	title = {Road {Bank} {Estimation} on {Uneven} {Terrain} for {Unmanned} {Ground} {Vehicles}},
	isbn = {978-0-7918-4418-2},
	url = {https://asmedigitalcollection.asme.org/DSCC/proceedings/DSCC2010/44182/849/348883},
	doi = {10.1115/DSCC2010-4196},
	abstract = {Knowledge of non-negligible bank angle is important for preventing rollover on uneven terrain. This article shows the effect of uneven terrain on rollover and explores a method to calculate the bank of the uneven terrain. An Extended Kalman Filter (EKF) is implemented to estimate the total roll of the vehicle. Information on the relative roll of the vehicle is acquired from suspension geometry and suspension deflections. The combination of EKF estimated roll and measured suspension deflections yields an estimate of the road bank angle.},
	urldate = {2024-06-20},
	booktitle = {{ASME} 2010 {Dynamic} {Systems} and {Control} {Conference}, {Volume} 2},
	publisher = {ASMEDC},
	author = {Brown, Lowell S. and Dawkins, Jeremy J. and Hill, Ryan S. and Bevly, David M.},
	month = jan,
	year = {2010},
	pages = {849--855},
}

Knowledge of non-negligible bank angle is important for preventing rollover on uneven terrain. This article shows the effect of uneven terrain on rollover and explores a method to calculate the bank of the uneven terrain. An Extended Kalman Filter (EKF) is implemented to estimate the total roll of the vehicle. Information on the relative roll of the vehicle is acquired from suspension geometry and suspension deflections. The combination of EKF estimated roll and measured suspension deflections yields an estimate of the road bank angle.

@inproceedings{britt_state_2010,
	address = {Cambridge, Massachusetts, USA},
	title = {A {State} {Machine} {Controller} for the {Autonomous} {Guidance} of a {Trained} {Canine}},
	isbn = {978-0-7918-4417-5 978-0-7918-3884-6},
	url = {https://asmedigitalcollection.asme.org/DSCC/proceedings/DSCC2010/44175/825/345401},
	doi = {10.1115/DSCC2010-4020},
	abstract = {This work demonstrates the autonomous command of a trained search canine to multiple waypoints using a novel state machine control algorithm. A hardware system is utilized in order to interface with the Global Position Satellite (GPS) system and with a tone and vibration generator for the purpose of accurately navigating and commanding the canine. An operational control algorithm for autonomous guidance of the canine is described in detail. Empirical results of an autonomously commanded canine are demonstrated with an 73\% mission success rate for simple paths and a 62\% mission success rate for complex paths. This work demonstrates a novel way to expand the capabilities of canines in a wide variety of missions, including search and detection.},
	urldate = {2024-06-20},
	booktitle = {{ASME} 2010 {Dynamic} {Systems} and {Control} {Conference}, {Volume} 1},
	publisher = {ASMEDC},
	author = {Britt, Winard and Lyles, William and Bevly, David M.},
	month = jan,
	year = {2010},
	pages = {825--833},
}

This work demonstrates the autonomous command of a trained search canine to multiple waypoints using a novel state machine control algorithm. A hardware system is utilized in order to interface with the Global Position Satellite (GPS) system and with a tone and vibration generator for the purpose of accurately navigating and commanding the canine. An operational control algorithm for autonomous guidance of the canine is described in detail. Empirical results of an autonomously commanded canine are demonstrated with an 73% mission success rate for simple paths and a 62% mission success rate for complex paths. This work demonstrates a novel way to expand the capabilities of canines in a wide variety of missions, including search and detection.

@inproceedings{broderick_modeling_2010,
	address = {Cambridge, Massachusetts, USA},
	title = {Modeling {Vehicle} {Lateral} {Dynamics} by {Gaussian} {Processes}},
	isbn = {978-0-7918-4418-2},
	url = {https://asmedigitalcollection.asme.org/DSCC/proceedings/DSCC2010/44182/827/348867},
	doi = {10.1115/DSCC2010-4151},
	abstract = {A method of modeling a vehicle’s lateral dynamics is investigated. Gaussian processes (GP) are used to estimate the side slip and yaw rate of the vehicle. A method of clustering the inputs to the GPs is also investigated and the effects of a key parameter, the clustering threshold, are examined. Sensitivity of this parameter is considered and a compromise is found between model accuracy and computation time. A discussion of how these methods can be extended to online adaptation of the estimators is included.},
	urldate = {2024-06-20},
	booktitle = {{ASME} 2010 {Dynamic} {Systems} and {Control} {Conference}, {Volume} 2},
	publisher = {ASMEDC},
	author = {Broderick, David J. and Bevly, David M. and Hung, John Y.},
	month = jan,
	year = {2010},
	pages = {827--834},
}

A method of modeling a vehicle’s lateral dynamics is investigated. Gaussian processes (GP) are used to estimate the side slip and yaw rate of the vehicle. A method of clustering the inputs to the GPs is also investigated and the effects of a key parameter, the clustering threshold, are examined. Sensitivity of this parameter is considered and a compromise is found between model accuracy and computation time. A discussion of how these methods can be extended to online adaptation of the estimators is included.

@inproceedings{martin_terrain_2010,
	title = {Terrain {Characterization} and {Feature} {Extraction} for {Automated} {Convoys}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=9153},
	abstract = {Autonomous ground vehicle systems require numerous sensors in order to navigate through hazardous environments. In order for a single vehicle to detect obstacles or hazards and plan its path, it is not uncommon to see an autonomous vehicle with several LiDARs, cameras, and other specialized sensors. Passing information from the leading vehicle allows fewer sensors to be used on following vehicles in the convoy. The sharing of sensor information does raise an issue in terms of data management and storage. Passing raw measurement data from sensors such as a LiDAR can quickly become a computational burden. Instead it is more desirable to pass only the information that is pertinent to the following vehicle. The focus of this work is to develop methodologies to evaluate the terrain and extract features along the vehicle path. Of particular interest are those features which can be hazardous to a following vehicle, or those features which can aid in the planning of the following vehicles path. Ground scans from a LiDAR are used to identify objects which help determine the most appropriate path for the follower to take. The roughness of the terrain is characterized using Power Spectral Density (PSD) and Root mean squared elevation (RMSE). An algorithm based on the Wavelet transform is developed to identify important features which can be used to aid in the vehicle navigation.},
	language = {en},
	urldate = {2024-06-20},
	author = {Martin, S. M. and Dawkins, J. J. and Travis, W. E. and Bevly, D. M.},
	month = sep,
	year = {2010},
	pages = {256--265},
}

Autonomous ground vehicle systems require numerous sensors in order to navigate through hazardous environments. In order for a single vehicle to detect obstacles or hazards and plan its path, it is not uncommon to see an autonomous vehicle with several LiDARs, cameras, and other specialized sensors. Passing information from the leading vehicle allows fewer sensors to be used on following vehicles in the convoy. The sharing of sensor information does raise an issue in terms of data management and storage. Passing raw measurement data from sensors such as a LiDAR can quickly become a computational burden. Instead it is more desirable to pass only the information that is pertinent to the following vehicle. The focus of this work is to develop methodologies to evaluate the terrain and extract features along the vehicle path. Of particular interest are those features which can be hazardous to a following vehicle, or those features which can aid in the planning of the following vehicles path. Ground scans from a LiDAR are used to identify objects which help determine the most appropriate path for the follower to take. The roughness of the terrain is characterized using Power Spectral Density (PSD) and Root mean squared elevation (RMSE). An algorithm based on the Wavelet transform is developed to identify important features which can be used to aid in the vehicle navigation.

@inproceedings{britt_lidar_2010,
	title = {Lidar attitude estimation for vehicle safety systems},
	url = {https://ieeexplore.ieee.org/abstract/document/5507283},
	doi = {10.1109/PLANS.2010.5507283},
	abstract = {This paper presents two techniques for determining vehicle pitch and roll with a 3-D lidar which will first auto-calibrate itself to the vehicle's axes. The first method presented is based on Euler angles and the second on Gaussian Processes. A 3-antenna Septentrio GPS receiver is used to asses system performance.},
	urldate = {2024-06-20},
	booktitle = {{IEEE}/{ION} {Position}, {Location} and {Navigation} {Symposium}},
	author = {Britt, Jordan and Broderick, David J. and Bevly, David and Hung, John},
	month = may,
	year = {2010},
	note = {ISSN: 2153-3598},
	keywords = {Acoustic beams, Attitude, Calibration, Gaussian Processes, Gaussian processes, Global Positioning System, Laser radar, Lidar, Position measurement, Sensor systems, Sonar detection, Vehicle safety, Vehicles},
	pages = {1226--1231},
}

This paper presents two techniques for determining vehicle pitch and roll with a 3-D lidar which will first auto-calibrate itself to the vehicle's axes. The first method presented is based on Euler angles and the second on Gaussian Processes. A 3-antenna Septentrio GPS receiver is used to asses system performance.

@inproceedings{allen_relating_2010,
	title = {Relating local vision measurements to global navigation satellite systems using waypoint based maps},
	url = {https://ieeexplore.ieee.org/abstract/document/5507280},
	doi = {10.1109/PLANS.2010.5507280},
	abstract = {Roughly 50\% of all the traffic fatalities are due to lane departures. There is great interest in advanced driver assistance systems that prevent unintended lane departure. Currently there are passive lane detection systems that warn the driver of unintended land departure know as land departure warning (LDW) systems which rely on cameras to track lane markings. LDW systems base solely off camera measurements are prone to failures due to poor environmental lighting or poor lane marking coverage. Combining the measurements from multiple sensors will create a much more robust LDW system that is not prone to failures. The purpose of this paper is to present a method that involves combining measurements from global navigation satellite systems (GNSS) with camera and Light Detection and Ranging (LiDAR) measurements for lane level positioning. These measurements are blended with IMU data using a Kalman filter. When using a Kalman filter to blend the data, the states of the filter are based in a global coordinate frame because GNSS measurements are given in a global coordinate frame. Lane position measurements are given in a local coordinate frame; therefore, lane position measurements must be related to the global coordinate frame in order to incorporate them into the navigation filter. This paper presents a method of relating local vision measurements to the global coordinate frame. This method can be used in conjunction with pre-existing global based navigation filters. The vision measurements are related to the global coordinate frame using a waypoint map. This method is dependent on the choice of global coordinate frame. Navigation filters based in two popular global coordinate frame are discussed in this paper. The first is the North, East, Down (NED) coordinate frame. The second is the Earth Centered Earth Fixed (ECEF) coordinate frame.},
	urldate = {2024-06-20},
	booktitle = {{IEEE}/{ION} {Position}, {Location} and {Navigation} {Symposium}},
	author = {Allen, John W. and Bevly, David M.},
	month = may,
	year = {2010},
	note = {ISSN: 2153-3598},
	keywords = {Cameras, Filters, Global Positioning System, Image edge detection, Laser radar, Navigation, Position measurement, Reflectivity, Robustness, Vehicles},
	pages = {1204--1211},
}

Roughly 50% of all the traffic fatalities are due to lane departures. There is great interest in advanced driver assistance systems that prevent unintended lane departure. Currently there are passive lane detection systems that warn the driver of unintended land departure know as land departure warning (LDW) systems which rely on cameras to track lane markings. LDW systems base solely off camera measurements are prone to failures due to poor environmental lighting or poor lane marking coverage. Combining the measurements from multiple sensors will create a much more robust LDW system that is not prone to failures. The purpose of this paper is to present a method that involves combining measurements from global navigation satellite systems (GNSS) with camera and Light Detection and Ranging (LiDAR) measurements for lane level positioning. These measurements are blended with IMU data using a Kalman filter. When using a Kalman filter to blend the data, the states of the filter are based in a global coordinate frame because GNSS measurements are given in a global coordinate frame. Lane position measurements are given in a local coordinate frame; therefore, lane position measurements must be related to the global coordinate frame in order to incorporate them into the navigation filter. This paper presents a method of relating local vision measurements to the global coordinate frame. This method can be used in conjunction with pre-existing global based navigation filters. The vision measurements are related to the global coordinate frame using a waypoint map. This method is dependent on the choice of global coordinate frame. Navigation filters based in two popular global coordinate frame are discussed in this paper. The first is the North, East, Down (NED) coordinate frame. The second is the Earth Centered Earth Fixed (ECEF) coordinate frame.

@inproceedings{allen_performance_2010,
	title = {Performance {Evaluation} of {Range} {Information} {Provided} by {Dedicated} {Short}-{Range} {Communication} ({DSRC}) {Radios}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=9282},
	abstract = {Dedicated short-range communications (DSRC) is a wireless communication protocol designed for automotive use. DSRC will also play a part in major changes to ground vehicle GNSS, if DSRC can provide ranges between two radios. Once the DSRC infrastructure is in place, every vehicle and intersection within a small range of a vehicle navigation system will become a extra "ground-based satellite" that can be used to update the navigation filter. This new method of ranging will be very useful in environments where limited GPS satellites are available. These areas include dense urban environments, areas of heavy foliage, and tunnels. This paper will cover the performance of DSRC based ranging. Two Multiband Configurable Networking Units (MCNU) provided by Kapsch will be used to evaluate the performance of DSRC based ranging. This paper will also cover how these ranges can be incorporated into a traditional global based navigation system. In order to test the performance of the radio based ranging, real data from the NCAT test track in Opelika, Alabama will be used. The NCAT track has a GPS base station broadcasting RTK corrections. The corrected GPS position and velocity is used as a baseline to judge error.},
	language = {en},
	urldate = {2024-06-20},
	author = {Allen, J. W. and Bevly, D. M.},
	month = sep,
	year = {2010},
	pages = {1631--1635},
}

Dedicated short-range communications (DSRC) is a wireless communication protocol designed for automotive use. DSRC will also play a part in major changes to ground vehicle GNSS, if DSRC can provide ranges between two radios. Once the DSRC infrastructure is in place, every vehicle and intersection within a small range of a vehicle navigation system will become a extra "ground-based satellite" that can be used to update the navigation filter. This new method of ranging will be very useful in environments where limited GPS satellites are available. These areas include dense urban environments, areas of heavy foliage, and tunnels. This paper will cover the performance of DSRC based ranging. Two Multiband Configurable Networking Units (MCNU) provided by Kapsch will be used to evaluate the performance of DSRC based ranging. This paper will also cover how these ranges can be incorporated into a traditional global based navigation system. In order to test the performance of the radio based ranging, real data from the NCAT test track in Opelika, Alabama will be used. The NCAT track has a GPS base station broadcasting RTK corrections. The corrected GPS position and velocity is used as a baseline to judge error.

@unpublished{nevin_registration_2009,
	type = {thesis},
	title = {Registration and {Tracking} of {Objects} with {Computer} {Vision} for {Autonomous} {Vehicles}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/1633},
	abstract = {For this research, an autonomous leader-follower vehicle caravan is being designed using computer vision. The focus of this research is to investigate computer vision methods of identifying objects detected by the leader vehicle and determining the follower vehicle' s position relative to the objects. Many object registration and tracking methods are presented in this paper such as Hough transforms, optical flow, and normalized cross correlation. A novel statistical-gradient method is presented to combine feature based methods and area based methods for object registration and tracking. These methods are evaluated against both synthetic and captured video data. This registration method is shown to be effective with both synthetic data and acquired data.},
	language = {en},
	urldate = {2024-06-25},
	author = {Nevin, Andrew},
	month = apr,
	year = {2009},
	note = {Accepted: 2009-04-15T15:44:42Z},
}

For this research, an autonomous leader-follower vehicle caravan is being designed using computer vision. The focus of this research is to investigate computer vision methods of identifying objects detected by the leader vehicle and determining the follower vehicle' s position relative to the objects. Many object registration and tracking methods are presented in this paper such as Hough transforms, optical flow, and normalized cross correlation. A novel statistical-gradient method is presented to combine feature based methods and area based methods for object registration and tracking. These methods are evaluated against both synthetic and captured video data. This registration method is shown to be effective with both synthetic data and acquired data.

@unpublished{britt_software_2009,
	title = {A {Software} and {Hardware} {System} for the {Autonomous} {Control} and {Navigation} of a {Trained} {Canine}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/1800},
	abstract = {This dissertation demonstrates the autonomous command and navigation of a trained
canine to multiple waypoints. A system is described consisting of a canine that can be
guided autonomously to a number of waypoints by an automatic software control algorithm.
A hardware system has been developed in order to interface with GPS, accelerometers,
gyroscopes, magnetometers, and tone and vibration generators for the purpose of accurately
commanding and dictating the motion, path, and commands given to a canine. A canine
has been trained to e ectively follow audio and vibration commands for guidance with a
high degree of accuracy (71\% mission success for simple paths and 63\% mission success for
complex paths). Both a Neural Networks approach and a State Machine Based approach
to canine anomaly detection are presented, as well as strategies for anomaly correction. An
operational control algorithm for autonomous guidance of the canine is described in detail.
Finally, empirical results of an autonomously commanded canine are demonstrated with
an 73\% mission success rate for simple paths and a 62\% mission success rate for complex
paths.},
	language = {en},
	urldate = {2024-06-25},
	author = {Britt, Winard},
	month = jul,
	year = {2009},
	note = {Accepted: 2009-07-20T20:19:01Z},
}

This dissertation demonstrates the autonomous command and navigation of a trained canine to multiple waypoints. A system is described consisting of a canine that can be guided autonomously to a number of waypoints by an automatic software control algorithm. A hardware system has been developed in order to interface with GPS, accelerometers, gyroscopes, magnetometers, and tone and vibration generators for the purpose of accurately commanding and dictating the motion, path, and commands given to a canine. A canine has been trained to e ectively follow audio and vibration commands for guidance with a high degree of accuracy (71% mission success for simple paths and 63% mission success for complex paths). Both a Neural Networks approach and a State Machine Based approach to canine anomaly detection are presented, as well as strategies for anomaly correction. An operational control algorithm for autonomous guidance of the canine is described in detail. Finally, empirical results of an autonomously commanded canine are demonstrated with an 73% mission success rate for simple paths and a 62% mission success rate for complex paths.

@unpublished{lashley_modeling_2009,
	title = {Modeling and {Performance} {Analysis} of {GPS} {Vector} {Tracking} {Algorithms}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/2009},
	abstract = {This dissertation provides a detailed analysis of GPS vector tracking algorithms and the
advantages they have over traditional receiver architectures. Standard GPS receivers use a
decentralized architecture that separates the tasks of signal tracking and position/velocity
estimation. Vector tracking algorithms combine the two tasks into a single algorithm. The
signals from the various satellites are processed collectively through a Kalman filter.
The advantages of vector tracking over traditional, scalar tracking methods are thoroughly
investigated. A method for making a valid comparison between vector and scalar
tracking loops is developed. This technique avoids the ambiguities encountered when attempting
to make a valid comparison between tracking loops (which are characterized by
noise bandwidths and loop order) and the Kalman filters (which are characterized by process
and measurement noise covariance matrices) that are used by vector tracking algorithms.
The improvement in performance offered by vector tracking is calculated in multiple different
scenarios.
Rule of thumb analysis techniques for scalar Frequency Lock Loops (FLL) are extended
to the vector tracking case. The analysis tools provide a simple method for analyzing the performance of vector tracking loops. The analysis tools are verified using Monte Carlo
simulations. Monte Carlo simulations are also used to study the effects of carrier to noise
power density (C/No) ratio estimation and the advantage offered by vector tracking over
scalar tracking. The improvement from vector tracking ranges from 2.4 to 6.2 dB in various
scenarios.
The difference in the performance of the three vector tracking architectures is analyzed.
The effects of using a federated architecture with and without information sharing between
the receiver’s channels are studied. A combination of covariance analysis and Monte Carlo
simulation is used to analyze the performance of the three algorithms. The federated algorithm
without information sharing performs poorer than the other two architectures.
However, at low C/N0 ratios the difference in the performance of the three algorithms
becomes virtually zero.
The analysis of different vector tracking architectures is then extended to an analysis
of different Deeply Integrated (DI) architectures. The effects of using a federated filtering
architecture on DI’s performance are investigated. Covariance analysis and Monte Carlo
simulation are also used to study the performance of the different DI algorithms. The
results from the DI analysis mirror the results from the analysis of different vector tracking
algorithms. The different DI architectures exhibit the same performance at low C/N0 ratios.
The vector tracking algorithms are also implemented in MATLAB. The algorithms
are tested using data collected from an environment with dense foliage (having widely
fluctuating signal levels) and from an urban canyon type environment. The performance of
the vector tracking algorithms is compared to that of a NovAtel ProPak-V3 receiver in the same scenarios. The vector tracking algorithms provide near continuous coverage through
both environments while the NovAtel receiver exhibits periods of prolonged outages.},
	language = {en},
	urldate = {2024-06-25},
	author = {Lashley, Matthew},
	month = dec,
	year = {2009},
	note = {Accepted: 2009-12-17T15:21:17Z},
}

This dissertation provides a detailed analysis of GPS vector tracking algorithms and the advantages they have over traditional receiver architectures. Standard GPS receivers use a decentralized architecture that separates the tasks of signal tracking and position/velocity estimation. Vector tracking algorithms combine the two tasks into a single algorithm. The signals from the various satellites are processed collectively through a Kalman filter. The advantages of vector tracking over traditional, scalar tracking methods are thoroughly investigated. A method for making a valid comparison between vector and scalar tracking loops is developed. This technique avoids the ambiguities encountered when attempting to make a valid comparison between tracking loops (which are characterized by noise bandwidths and loop order) and the Kalman filters (which are characterized by process and measurement noise covariance matrices) that are used by vector tracking algorithms. The improvement in performance offered by vector tracking is calculated in multiple different scenarios. Rule of thumb analysis techniques for scalar Frequency Lock Loops (FLL) are extended to the vector tracking case. The analysis tools provide a simple method for analyzing the performance of vector tracking loops. The analysis tools are verified using Monte Carlo simulations. Monte Carlo simulations are also used to study the effects of carrier to noise power density (C/No) ratio estimation and the advantage offered by vector tracking over scalar tracking. The improvement from vector tracking ranges from 2.4 to 6.2 dB in various scenarios. The difference in the performance of the three vector tracking architectures is analyzed. The effects of using a federated architecture with and without information sharing between the receiver’s channels are studied. A combination of covariance analysis and Monte Carlo simulation is used to analyze the performance of the three algorithms. The federated algorithm without information sharing performs poorer than the other two architectures. However, at low C/N0 ratios the difference in the performance of the three algorithms becomes virtually zero. The analysis of different vector tracking architectures is then extended to an analysis of different Deeply Integrated (DI) architectures. The effects of using a federated filtering architecture on DI’s performance are investigated. Covariance analysis and Monte Carlo simulation are also used to study the performance of the different DI algorithms. The results from the DI analysis mirror the results from the analysis of different vector tracking algorithms. The different DI architectures exhibit the same performance at low C/N0 ratios. The vector tracking algorithms are also implemented in MATLAB. The algorithms are tested using data collected from an environment with dense foliage (having widely fluctuating signal levels) and from an urban canyon type environment. The performance of the vector tracking algorithms is compared to that of a NovAtel ProPak-V3 receiver in the same scenarios. The vector tracking algorithms provide near continuous coverage through both environments while the NovAtel receiver exhibits periods of prolonged outages.

@inproceedings{miller_guided_2009,
	title = {Guided {K}-9 {Tracking} {Improvements} using {GPS}, {INS}, and {Magnetometers}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=8389},
	abstract = {A GPS/INS sensor suite, including magnetometers, was attached by a vest to a canine (K-9) in order to attain characteristic position and orientation data during typical canine behavioral motion. For better accuracy, the sensors were combined using a hybrid Extended Kalman Filter (EKF) and then examined to see if the orientation EKF output correctly portrayed the canine motions when magnetometers were present and GPS outages occurred. Special tuning of the EKF was required due to the unique motion characteristics inherent in canines. However, the EKF was found to be effective in achieving accurate orientation tracking results for the canine during GPS outages. Results show that the low-cost GPS/INS system with magnetometers can provide information about the canine’s motion, including the canine’s current position and heading.},
	language = {en},
	urldate = {2024-06-20},
	author = {Miller, Jeff and Bevly, David M.},
	month = jan,
	year = {2009},
	pages = {1038--1047},
}

A GPS/INS sensor suite, including magnetometers, was attached by a vest to a canine (K-9) in order to attain characteristic position and orientation data during typical canine behavioral motion. For better accuracy, the sensors were combined using a hybrid Extended Kalman Filter (EKF) and then examined to see if the orientation EKF output correctly portrayed the canine motions when magnetometers were present and GPS outages occurred. Special tuning of the EKF was required due to the unique motion characteristics inherent in canines. However, the EKF was found to be effective in achieving accurate orientation tracking results for the canine during GPS outages. Results show that the low-cost GPS/INS system with magnetometers can provide information about the canine’s motion, including the canine’s current position and heading.

@inproceedings{travis_performance_2009,
	title = {Performance {Analysis} of a {Closely} {Coupled} {GPS}/{INS} {Relative} {Positioning} {Architecture} for {Automated} {Ground} {Vehicle} {Convoys}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=8385},
	abstract = {A relative positioning software architecture incorporating inertial, range, and phase measurements has been developed to enhance the ability and accuracy of path following for autonomous ground vehicles in a convoy. GPS carrier measurements are fused with INS systems on board each vehicle to exploit the temporal and spacial error correlation of GPS signals within the same region and determine a high precision relative position vector between moving vehicles in the convoy. A discussion of the difficulties encountered in a ground vehicle environment is presented, along with the derivation of the algorithms which are to run on the convoy vehicles. An increase in robustness of the position solution is seen, and the relative position solution shows the ability to bridge short GPS outages.},
	language = {en},
	urldate = {2024-06-20},
	author = {Travis, William and Bevly, David M.},
	month = jan,
	year = {2009},
	pages = {999--1008},
}

A relative positioning software architecture incorporating inertial, range, and phase measurements has been developed to enhance the ability and accuracy of path following for autonomous ground vehicles in a convoy. GPS carrier measurements are fused with INS systems on board each vehicle to exploit the temporal and spacial error correlation of GPS signals within the same region and determine a high precision relative position vector between moving vehicles in the convoy. A discussion of the difficulties encountered in a ground vehicle environment is presented, along with the derivation of the algorithms which are to run on the convoy vehicles. An increase in robustness of the position solution is seen, and the relative position solution shows the ability to bridge short GPS outages.

@inproceedings{rose_vehicle_2009,
	title = {Vehicle {Lane} {Position} {Estimation} with {Camera} {Vision} using {Bounded} {Polynomial} {Interpolated} {Lines}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=8293},
	abstract = {Applications of camera vision, such as lane departure warning systems, are limited by the quality of the frame image and the information contained within each frame. One common feature extraction technique in image processing is the use of the Hough transform, which can be used to extract lines from an image. The detected lane marking lines are used in the interpolation of a 2nd order polynomial to estimate the shape of the lane marking’s curve in the image. However, blurry frames, additional road markings on the ground, and adverse weather conditions can ruin detection of these valid lane lines. To eliminate erroneous lines, a technique has been employed which bounds the previously detected 2nd order polynomial with two other polynomials that are equidistant from the original polynomial. These bounding curves employ similar characteristics as the original curve; therefore, the valid lane marking should be detected within the bounded area given smooth transitions between each frame. The effects of erroneous lines within this bounded area can be reduced by employing a Kalman filter on the coefficients of the 2nd order polynomial. The filter also allows for smooth transitions between curved and straight roads. The measurement of the position within the lane is carried out by determining the number of pixels from the center of the image and the estimated lane marking. This measurement value can then be converted to its real world equivalent and used to estimate the position of the vehicle within the lane. This technique is verified by comparing lateral distance measurements from RTK GPS measurements and the measurements from a camera. Results will show that this method performs well on straight roads but fails to perform well on curves.},
	language = {en},
	urldate = {2024-06-20},
	author = {Rose, Christopher and Bevly, David M.},
	month = jan,
	year = {2009},
	pages = {102--108},
}

Applications of camera vision, such as lane departure warning systems, are limited by the quality of the frame image and the information contained within each frame. One common feature extraction technique in image processing is the use of the Hough transform, which can be used to extract lines from an image. The detected lane marking lines are used in the interpolation of a 2nd order polynomial to estimate the shape of the lane marking’s curve in the image. However, blurry frames, additional road markings on the ground, and adverse weather conditions can ruin detection of these valid lane lines. To eliminate erroneous lines, a technique has been employed which bounds the previously detected 2nd order polynomial with two other polynomials that are equidistant from the original polynomial. These bounding curves employ similar characteristics as the original curve; therefore, the valid lane marking should be detected within the bounded area given smooth transitions between each frame. The effects of erroneous lines within this bounded area can be reduced by employing a Kalman filter on the coefficients of the 2nd order polynomial. The filter also allows for smooth transitions between curved and straight roads. The measurement of the position within the lane is carried out by determining the number of pixels from the center of the image and the estimated lane marking. This measurement value can then be converted to its real world equivalent and used to estimate the position of the vehicle within the lane. This technique is verified by comparing lateral distance measurements from RTK GPS measurements and the measurements from a camera. Results will show that this method performs well on straight roads but fails to perform well on curves.

@inproceedings{clark_fde_2009,
	title = {{FDE} {Implementations} for a {Low}-{Cost} {GPS}/{INS} {Module}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=8504},
	abstract = {This paper describes the implementation details of fault detection and exclusion (FDE) methods for possible use in a low-cost GPS/INS module. The use of a coupled system has been previously considered for improving navigation in GPS difficult environments. Such environments adversely affect the satellite signals received by a navigation system. Integration with an INS allows for higher output rate as well as improved coasting through GPS signal blockage. Previous work has shown that the inclusion of a FDE algorithm allows for the removal of faulty GPS measurements that tend to corrupt the navigation solution. This work gives analysis of several FDE methods both from the standpoint of performance and efficiency. The resulting goal of this work is the details of a realtime GPS/INS module with FDE improvements. The module design requirements are specified for use in low-cost applications. Since operation in vehicular environments is desired, meter-level accuracy is investigated so that approximate lane-level information could be available to the user of the navigation system. The FDE methods under consideration both have snapshot and sequential implementations. The snapshot methods are performed independently between measurement epochs and thus do not suffer from undetected errors that corrupt the states. Sequential methods are able to detect a wider variety of errors but are delayed in acting on failure conditions. These two implementations are compared for the normalized innovation method and the direct consistency check method. The normalized innovation technique is a comparison of the resulting new information provided by a measurement to a normalized threshold. The threshold is set to detect measurements that do not statistically conform to the expected accuracy. The direct consistency check algorithm performs a comparison of a measurement to what the measurement is expected to be given the removal of the measurement from the estimation. Faults are then detected and removed when inconsistencies are found. These methods are considered for use in the GPS difficult environments. The comparison of these methods is accomplished by the design and assembly of the GPS/INS module. This module is then used to log the required data for initial postprocessing. Various data collection locations considered include open-sky, urban canyon, and heavy foliage areas. The integration and FDE algorithms are then run on the same data sets and fault detection occurrences compared among the methods. Processing time is also monitored for the post-processing to generate efficiency results. The details are then given to implement the chosen method in realtime on a low-cost GPS/INS module. Due to the quickly changing nature of the GPS errors in difficult environments, the snapshot methods tend to provide faster detection of errors and thus improved performance. For faster implementation, the normalized innovation technique is selected to reduce load on the embedded navigation system. This choice allows for more flexibility in extending the module use. The result of this work is a navigation system implementable in real-time that provides improved positioning in GPS difficult environments. Many applications such as vehicle navigation and control benefit from improved performance in these situations. The inclusion of the low-cost requirement allows for more ubiquitous use of these results.},
	language = {en},
	urldate = {2024-06-20},
	author = {Clark, B. J. and Bevly, D. M.},
	month = sep,
	year = {2009},
	pages = {970--977},
}

This paper describes the implementation details of fault detection and exclusion (FDE) methods for possible use in a low-cost GPS/INS module. The use of a coupled system has been previously considered for improving navigation in GPS difficult environments. Such environments adversely affect the satellite signals received by a navigation system. Integration with an INS allows for higher output rate as well as improved coasting through GPS signal blockage. Previous work has shown that the inclusion of a FDE algorithm allows for the removal of faulty GPS measurements that tend to corrupt the navigation solution. This work gives analysis of several FDE methods both from the standpoint of performance and efficiency. The resulting goal of this work is the details of a realtime GPS/INS module with FDE improvements. The module design requirements are specified for use in low-cost applications. Since operation in vehicular environments is desired, meter-level accuracy is investigated so that approximate lane-level information could be available to the user of the navigation system. The FDE methods under consideration both have snapshot and sequential implementations. The snapshot methods are performed independently between measurement epochs and thus do not suffer from undetected errors that corrupt the states. Sequential methods are able to detect a wider variety of errors but are delayed in acting on failure conditions. These two implementations are compared for the normalized innovation method and the direct consistency check method. The normalized innovation technique is a comparison of the resulting new information provided by a measurement to a normalized threshold. The threshold is set to detect measurements that do not statistically conform to the expected accuracy. The direct consistency check algorithm performs a comparison of a measurement to what the measurement is expected to be given the removal of the measurement from the estimation. Faults are then detected and removed when inconsistencies are found. These methods are considered for use in the GPS difficult environments. The comparison of these methods is accomplished by the design and assembly of the GPS/INS module. This module is then used to log the required data for initial postprocessing. Various data collection locations considered include open-sky, urban canyon, and heavy foliage areas. The integration and FDE algorithms are then run on the same data sets and fault detection occurrences compared among the methods. Processing time is also monitored for the post-processing to generate efficiency results. The details are then given to implement the chosen method in realtime on a low-cost GPS/INS module. Due to the quickly changing nature of the GPS errors in difficult environments, the snapshot methods tend to provide faster detection of errors and thus improved performance. For faster implementation, the normalized innovation technique is selected to reduce load on the embedded navigation system. This choice allows for more flexibility in extending the module use. The result of this work is a navigation system implementable in real-time that provides improved positioning in GPS difficult environments. Many applications such as vehicle navigation and control benefit from improved performance in these situations. The inclusion of the low-cost requirement allows for more ubiquitous use of these results.

@inproceedings{rose_camera_2009,
	title = {Camera {Vision} and {Inertial} {Measurement} {Unit} {Sensor} {Fusion} for {Lane} {Detection} and {Tracking} {Using} {Polynomial} {Bounding} {Curves}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=8592},
	abstract = {This paper studies a technique for combining vision and inertial measurement unit (IMU) data to increase the reliability of lane departure warning systems. In this technique, 2nd order polynomials are used to model the likelihood area of the location of the lane marking position in the image as well as the lane itself. An IMU is used to predict the drift of these polynomials and the estimated lane marking when the lane markings can not be detected in the image. Subsequent frames where the lane marking is present results in faster convergence of the model on the lane marking due to a reduced number of detected erroneous lines. A technique to reduce the affect of untracked lane markings has been employed which bounds the previously detected 2nd order polynomial with two other polynomials within which lies the likelihood region of the next frame’s lane marking. These bounds employ similar characteristics as the original line; therefore, the lane marking should be detected within the bounded area given smooth transitions between each frame. An inertial measurement unit can provide accelerations and rotation rates of a vehicle. Using an extended Kalman filter, information from the IMU can be blended with the last known coefficients of the estimated lane marking to approximate the lane marking coefficients until the lane is detected. A measurement of the position within the lane can be carried out by determining the number of pixels from the center of the image and the estimated lane marking. This measurement value can then be converted to its real world equivalent and used to estimate the position of the vehicle within the lane.},
	language = {en},
	urldate = {2024-06-20},
	author = {Rose, C. and Bevly, D. M.},
	month = sep,
	year = {2009},
	pages = {1849--1857},
}

This paper studies a technique for combining vision and inertial measurement unit (IMU) data to increase the reliability of lane departure warning systems. In this technique, 2nd order polynomials are used to model the likelihood area of the location of the lane marking position in the image as well as the lane itself. An IMU is used to predict the drift of these polynomials and the estimated lane marking when the lane markings can not be detected in the image. Subsequent frames where the lane marking is present results in faster convergence of the model on the lane marking due to a reduced number of detected erroneous lines. A technique to reduce the affect of untracked lane markings has been employed which bounds the previously detected 2nd order polynomial with two other polynomials within which lies the likelihood region of the next frame’s lane marking. These bounds employ similar characteristics as the original line; therefore, the lane marking should be detected within the bounded area given smooth transitions between each frame. An inertial measurement unit can provide accelerations and rotation rates of a vehicle. Using an extended Kalman filter, information from the IMU can be blended with the last known coefficients of the estimated lane marking to approximate the lane marking coefficients until the lane is detected. A measurement of the position within the lane can be carried out by determining the number of pixels from the center of the image and the estimated lane marking. This measurement value can then be converted to its real world equivalent and used to estimate the position of the vehicle within the lane.

@inproceedings{allen_use_2009,
	title = {Use of {Vision} {Sensors} and {Lane} {Maps} to {Aid} {GPS}/{INS} under a {Limited} {GPS} {Satellite} {Constellation}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=8490},
	abstract = {One major issue in implementation of a GPS/INS navigation system is the decrease in positioning performance in urban canyons. An urban canyon is any location where GPS satellite signals are blocked or corrupted by tall buildings. Tall buildings surrounding a GPS antenna will cause a masking affect on the antenna. Satellites that are at a low elevation angle will be blocked by buildings. Many of the signals that actually arrive at the antenna are corrupted by delays caused by multipath. A closely coupled GPS/INS navigation system with fault detection and exclusion can be used to combat the issue of multipath in urban areas. This paper will present a method of using vision measurements and a lane map to constrain the navigation system and thus improve observability. Many modern GPS/INS navigation systems use a closely coupled architecture. A closely coupled navigation systems refers to a navigation systems that uses the pseudorange and pseudorange-rate measurements provided by a GPS receiver. A loosely coupled navigation system refers to a system that uses only the position and velocity reported by the GPS receiver. One advantage of a closely coupled architecture is its ability to provide limited IMU corrections while receiving measurements from less than four satellites. A loosely coupled architecture will provide no IMU corrections if the GPS receiver fails to track four or more satellites. Another advantage of the closely coupled system is the ability for the system designer to incorporate intelligent measurement rejection to reject bad pseudoranges and pseudorange-rates. A closely coupled GPS/INS system with fault detection and measurement rejection can be used in an urban environment to mitigate navigation errors. The fault detection and measurement rejection will insure that bad pseudoranges and pseudorange-rates will not be used to compute the navigation solution. Furthermore, a complex elevation mask can be used to reject measurements from satellites that are believed to be currently blocked by buildings. One issue with pseudorange measurement rejection is the possibility of loss of observability. If the number satellite measurements used falls under four, then the GPS/INS system will not be fully observable. Also, when using a limited number of satellite observations, the observability of the GPS/INS system is heavily affected by the geometry of the satellites used. This paper proposes a method to increase observability of a GPS/INS system operating under limited satellite coverage. Extra range measurements from vision sensors are used to supplement the GPS’s pseudorange and pseudorange-rate measurements. Both LiDAR and camera measurements are used to measure a vehicle’s lateral position in its current lane. The vision measurements provide local based positioning based of the lane. A map of the lane is used to relate the vision’s local positioning and the GPS’s global positioning. Also, constraining the navigation system’s height above the lane map is used to further aid observability. In order to test the performance of the navigation filter, real data from the NCAT test track in Opelika, Alabama will be used. The NCAT track has plenty of open sky; therefore, the solution using a full constellation of GPS satellites can be compared to the solution using only two GPS observations.},
	language = {en},
	urldate = {2024-06-20},
	author = {Allen, J. W. and Bevly, D. M.},
	month = sep,
	year = {2009},
	pages = {835--844},
}

One major issue in implementation of a GPS/INS navigation system is the decrease in positioning performance in urban canyons. An urban canyon is any location where GPS satellite signals are blocked or corrupted by tall buildings. Tall buildings surrounding a GPS antenna will cause a masking affect on the antenna. Satellites that are at a low elevation angle will be blocked by buildings. Many of the signals that actually arrive at the antenna are corrupted by delays caused by multipath. A closely coupled GPS/INS navigation system with fault detection and exclusion can be used to combat the issue of multipath in urban areas. This paper will present a method of using vision measurements and a lane map to constrain the navigation system and thus improve observability. Many modern GPS/INS navigation systems use a closely coupled architecture. A closely coupled navigation systems refers to a navigation systems that uses the pseudorange and pseudorange-rate measurements provided by a GPS receiver. A loosely coupled navigation system refers to a system that uses only the position and velocity reported by the GPS receiver. One advantage of a closely coupled architecture is its ability to provide limited IMU corrections while receiving measurements from less than four satellites. A loosely coupled architecture will provide no IMU corrections if the GPS receiver fails to track four or more satellites. Another advantage of the closely coupled system is the ability for the system designer to incorporate intelligent measurement rejection to reject bad pseudoranges and pseudorange-rates. A closely coupled GPS/INS system with fault detection and measurement rejection can be used in an urban environment to mitigate navigation errors. The fault detection and measurement rejection will insure that bad pseudoranges and pseudorange-rates will not be used to compute the navigation solution. Furthermore, a complex elevation mask can be used to reject measurements from satellites that are believed to be currently blocked by buildings. One issue with pseudorange measurement rejection is the possibility of loss of observability. If the number satellite measurements used falls under four, then the GPS/INS system will not be fully observable. Also, when using a limited number of satellite observations, the observability of the GPS/INS system is heavily affected by the geometry of the satellites used. This paper proposes a method to increase observability of a GPS/INS system operating under limited satellite coverage. Extra range measurements from vision sensors are used to supplement the GPS’s pseudorange and pseudorange-rate measurements. Both LiDAR and camera measurements are used to measure a vehicle’s lateral position in its current lane. The vision measurements provide local based positioning based of the lane. A map of the lane is used to relate the vision’s local positioning and the GPS’s global positioning. Also, constraining the navigation system’s height above the lane map is used to further aid observability. In order to test the performance of the navigation filter, real data from the NCAT test track in Opelika, Alabama will be used. The NCAT track has plenty of open sky; therefore, the solution using a full constellation of GPS satellites can be compared to the solution using only two GPS observations.

@inproceedings{ryan_robust_2009,
	title = {Robust sideslip estimation using {GPS} road grade sensing to replace a pitch rate sensor},
	url = {https://ieeexplore.ieee.org/document/5346320/;jsessionid=DBA6C0D19E98F550808E7DEED660D656},
	doi = {10.1109/ICSMC.2009.5346320},
	abstract = {This paper analyzes a promising method of road grade estimation for its potential use in aiding ground vehicle electronic stability control systems. The method in question incorporates GPS and motion sensors into a basic Kalman Filter model to achieve clean, high update estimates of the vertical and longitudinal velocity states from which the grade can be easily calculated. The knowledge of road grade is incorporated into a sideslip estimation scheme, replacing the pitch rate sensor, and the improvement in the sideslip estimate is evaluated. Simulated results are shown, as are results from using experimental data comparing this sideslip estimate with one obtained which utilizes the pitch rate gyro.},
	urldate = {2024-06-20},
	booktitle = {2009 {IEEE} {International} {Conference} on {Systems}, {Man} and {Cybernetics}},
	author = {Ryan, Jonathan and Bevly, David and Lu, Jianbo},
	month = oct,
	year = {2009},
	note = {ISSN: 1062-922X},
	keywords = {Control systems, Filtering, GPS/INS, Global Positioning System, Kalman Filtering, Kalman filters, Roads, Robustness, Sensor Reduction, Sensor systems, Stability, State estimation, Vehicle State Estimation, Vehicles},
	pages = {2026--2031},
}

This paper analyzes a promising method of road grade estimation for its potential use in aiding ground vehicle electronic stability control systems. The method in question incorporates GPS and motion sensors into a basic Kalman Filter model to achieve clean, high update estimates of the vertical and longitudinal velocity states from which the grade can be easily calculated. The knowledge of road grade is incorporated into a sideslip estimation scheme, replacing the pitch rate sensor, and the improvement in the sideslip estimate is evaluated. Simulated results are shown, as are results from using experimental data comparing this sideslip estimate with one obtained which utilizes the pitch rate gyro.

@inproceedings{dawkins_multiscale_2009,
	address = {Hollywood, California, USA},
	title = {Multiscale {Terrain} {Characterization} {Using} {Fourier} and {Wavelet} {Transforms} for {Unmanned} {Ground} {Vehicles}},
	isbn = {978-0-7918-4893-7},
	url = {https://asmedigitalcollection.asme.org/DSCC/proceedings/DSCC2009/48937/635/346792},
	doi = {10.1115/DSCC2009-2718},
	abstract = {This paper investigates the use of the Fourier transform and Wavelet transform as methods to supplement the more common root mean squared elevation and power spectral density methods of terrain characterization. Two dimensional terrain profiles were generated using the Weierstrass-Mandelbrot fractal equation. The Fourier and Wavelet transforms were used to decompose these terrains into a parameter set. A two degree of freedom quarter car model was used to evaluate the vehicle response before and after the terrain characterization. It was determined that the Fourier transform can be used to reduce the profile into the key frequency components. The Wavelet transform can effectively detect discontinuities of the profile and changes in the roughness of the profile. These two techniques can be added to current methods to yield a more robust terrain characterization.},
	urldate = {2024-06-20},
	booktitle = {{ASME} 2009 {Dynamic} {Systems} and {Control} {Conference}, {Volume} 2},
	publisher = {ASMEDC},
	author = {Dawkins, Jeremy J. and Bevly, David M. and Jackson, Robert L.},
	month = jan,
	year = {2009},
	pages = {635--642},
}

This paper investigates the use of the Fourier transform and Wavelet transform as methods to supplement the more common root mean squared elevation and power spectral density methods of terrain characterization. Two dimensional terrain profiles were generated using the Weierstrass-Mandelbrot fractal equation. The Fourier and Wavelet transforms were used to decompose these terrains into a parameter set. A two degree of freedom quarter car model was used to evaluate the vehicle response before and after the terrain characterization. It was determined that the Fourier transform can be used to reduce the profile into the key frequency components. The Wavelet transform can effectively detect discontinuities of the profile and changes in the roughness of the profile. These two techniques can be added to current methods to yield a more robust terrain characterization.

@inproceedings{nevin_landmark_2009,
	title = {Landmark {Extraction} using {Corner} {Detection} and {\textless}em{\textgreater}k{\textless}/em{\textgreater}-{Means} {Clustering} for {Autonomous} {Leader}-{Follower} {Caravan}},
	url = {https://www.actapress.com/Abstract.aspx?paperId=35549},
	abstract = {Extracting a landmark in a digital video sequence is vital for visual navigation.},
	urldate = {2024-06-20},
	publisher = {ACTA Press},
	author = {Nevin, A. B. and Bevly, D. M.},
	month = nov,
	year = {2009},
}

Extracting a landmark in a digital video sequence is vital for visual navigation.

@inproceedings{lyles_evolution_2009,
	title = {Evolution of {Parameters} for an {Autonomous} {Canine} {Control} {Algorithm}},
	url = {https://ieeexplore.ieee.org/abstract/document/5381343},
	doi = {10.1109/ICMLA.2009.100},
	abstract = {This paper demonstrates an evolutionary algorithm for the optimization of an autonomous control algorithm for a trained canine. Autonomous guidance is relevant because use of canines, though beneficial in many applications, is limited by the necessity of close human supervision. A rules-based expert system using GPS data was initially developed for this purpose. This rules-based system is not without limitations. Primarily, it takes a significant investment of trainer and developer time to derive appropriate values to use for control of the canine. A multi-objective fitness metric was developed to optimize for important parts of the control algorithm, and parameters of the algorithm were optimized using evolutionary computation. In simulations the evolved parameters fit the data better than the hand-tuned parameters, and preliminary field trials showed a 67\% mission success rate, which shows the feasibility of evolving parameters for the control algorithm.},
	urldate = {2024-06-20},
	booktitle = {2009 {International} {Conference} on {Machine} {Learning} and {Applications}},
	author = {Lyles, William and Britt, Winard and Bevly, David},
	month = dec,
	year = {2009},
	keywords = {Canine control, Computational modeling, Error correction, Evolutionary computation, Expert systems, Global Positioning System, Humans, Investments, Machine learning, Machine learning algorithms, Sensor phenomena and characterization, evolutionary algorithms, parameter optimization},
	pages = {699--704},
}

This paper demonstrates an evolutionary algorithm for the optimization of an autonomous control algorithm for a trained canine. Autonomous guidance is relevant because use of canines, though beneficial in many applications, is limited by the necessity of close human supervision. A rules-based expert system using GPS data was initially developed for this purpose. This rules-based system is not without limitations. Primarily, it takes a significant investment of trainer and developer time to derive appropriate values to use for control of the canine. A multi-objective fitness metric was developed to optimize for important parts of the control algorithm, and parameters of the algorithm were optimized using evolutionary computation. In simulations the evolved parameters fit the data better than the hand-tuned parameters, and preliminary field trials showed a 67% mission success rate, which shows the feasibility of evolving parameters for the control algorithm.

@inproceedings{britt_lane_2009,
	title = {Lane {Tracking} using {Multilayer} {Laser} {Scanner} to {Enhance} {Vehicle} {Navigation} and {Safety} {Systems}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=8340},
	abstract = {It is of great interest in advanced driver assistance systems to prevent lane departure warning. Over half of all traffic fatalities in 2007 were caused by unintended lane departure [1]. Lane departure warning (LDW) systems often include passive sensors such as cameras to detect the lane and warn the driver of a lane departure. The most critical element of any lane keeping assistance system is the availability of reliable lane position information. Currently available LDW systems have shown that cameras can provide lane position information; however these systems suffer from technical limitations in areas where lane markings may be missing or difficult to detect due to lighting, rain, or snow [3][4]. However, LiDAR (Light Detection and Ranging) can be used to supplement other LDW sensors by providing lane position data accurately and consistently even in cases of varying outdoor conditions. It can provide additional robustness to a navigation solution by providing a lane position in the case of GPS outages. The objective of this research is to show that a multilayer LiDAR is capable of detecting and tracking lane markings that could supplement a LDW or on road navigation system. This will be realized using an Ibeo multilayer laser scanner that is capable measuring both distance and reflectivity data. The algorithm implemented is operating using the principle that the lane’s surface is less reflective than the lane markings [6]. Therefore points of high reflectivity of the scan act as potential lane markings. Based on the distance to the lane markings, the user’s position in the lane can be determined which will act as supplemental information to a navigation or safety system. Currently lane markings are capable of being found during post processing on both static and dynamic tests. Dynamic real-time data was taken at a NCAT test track aboard a Hyundai Sonata. LiDAR results of these tests were overlaid onto vision data, which were acquired simultaneously with the LiDAR data for a rough visual metric. Additionally the test track previously mentioned has been surveyed and will serve as a truth measurement in order to validate the methods used to acquire and track lane markings. This paper will cover in-depth the algorithm and processes used to acquire lane markings as well as techniques used to mitigate false readings.},
	language = {en},
	urldate = {2024-06-20},
	author = {Britt, Jordan H. and Bevly, David M.},
	month = jan,
	year = {2009},
	pages = {629--634},
}

It is of great interest in advanced driver assistance systems to prevent lane departure warning. Over half of all traffic fatalities in 2007 were caused by unintended lane departure [1]. Lane departure warning (LDW) systems often include passive sensors such as cameras to detect the lane and warn the driver of a lane departure. The most critical element of any lane keeping assistance system is the availability of reliable lane position information. Currently available LDW systems have shown that cameras can provide lane position information; however these systems suffer from technical limitations in areas where lane markings may be missing or difficult to detect due to lighting, rain, or snow [3][4]. However, LiDAR (Light Detection and Ranging) can be used to supplement other LDW sensors by providing lane position data accurately and consistently even in cases of varying outdoor conditions. It can provide additional robustness to a navigation solution by providing a lane position in the case of GPS outages. The objective of this research is to show that a multilayer LiDAR is capable of detecting and tracking lane markings that could supplement a LDW or on road navigation system. This will be realized using an Ibeo multilayer laser scanner that is capable measuring both distance and reflectivity data. The algorithm implemented is operating using the principle that the lane’s surface is less reflective than the lane markings [6]. Therefore points of high reflectivity of the scan act as potential lane markings. Based on the distance to the lane markings, the user’s position in the lane can be determined which will act as supplemental information to a navigation or safety system. Currently lane markings are capable of being found during post processing on both static and dynamic tests. Dynamic real-time data was taken at a NCAT test track aboard a Hyundai Sonata. LiDAR results of these tests were overlaid onto vision data, which were acquired simultaneously with the LiDAR data for a rough visual metric. Additionally the test track previously mentioned has been surveyed and will serve as a truth measurement in order to validate the methods used to acquire and track lane markings. This paper will cover in-depth the algorithm and processes used to acquire lane markings as well as techniques used to mitigate false readings.

@inproceedings{allen_intelligent_2009,
	title = {Intelligent {Multi}-{Sensor} {Measurements} to {Enhance} {Vehicle} {Navigation} and {Safety} {Systems}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=8290},
	abstract = {Nearly 50\% of all the traffic fatalities are due to accidental lane departures. Therefore, there is great interest in advanced driver assistance systems to prevent unintended lane departures. The purpose of this paper is to present a method of lane positioning that involves combining a GPS/IMU navigation system with camera and Light Detection and Ranging (LiDAR) measurements. A discrete Kalman filter is implemented as the navigation filter used to combine all the measurements. The navigation coordinate frame is a coordinate frame attached to the road. The camera and LiDAR are assumed to give a measurement of the vehicle’s current offset from the center of the current lane. This measurement directly corresponds to the y-axis of the navigation coordinate frame. The IMU used has 3 accelerometer axis and 3 gyros; however, only 2 accelerometers and 1 gyro were used for the navigation filter. Many vehicles come standard with a similar IMU set up for stability control. Many issues become apparent when working with a shifting navigation frame. Measurements from the GPS must be mapped into the road coordinate frame. This involves a transformation from earth centered earth fixed (ECEF) coordinates to the road frame’s coordinates. Also, the states of the navigation filter need to be updated when shifting to the next road coordinate frame. The largest implementation hurdle is obtaining a lane map. Current survey techniques are slow and require road closure. There are also issues with how long a road frame can be without adding error to the system. A road frame that is too long in a turn will cause error. The surveyed section of road used for the paper is split into road coordinate frames with an average length of around 10 m.},
	language = {en},
	urldate = {2024-06-20},
	author = {Allen, John W. and Britt, Jordan H. and Rose, Christopher J. and Bevly, David M.},
	month = jan,
	year = {2009},
	pages = {74--83},
}

Nearly 50% of all the traffic fatalities are due to accidental lane departures. Therefore, there is great interest in advanced driver assistance systems to prevent unintended lane departures. The purpose of this paper is to present a method of lane positioning that involves combining a GPS/IMU navigation system with camera and Light Detection and Ranging (LiDAR) measurements. A discrete Kalman filter is implemented as the navigation filter used to combine all the measurements. The navigation coordinate frame is a coordinate frame attached to the road. The camera and LiDAR are assumed to give a measurement of the vehicle’s current offset from the center of the current lane. This measurement directly corresponds to the y-axis of the navigation coordinate frame. The IMU used has 3 accelerometer axis and 3 gyros; however, only 2 accelerometers and 1 gyro were used for the navigation filter. Many vehicles come standard with a similar IMU set up for stability control. Many issues become apparent when working with a shifting navigation frame. Measurements from the GPS must be mapped into the road coordinate frame. This involves a transformation from earth centered earth fixed (ECEF) coordinates to the road frame’s coordinates. Also, the states of the navigation filter need to be updated when shifting to the next road coordinate frame. The largest implementation hurdle is obtaining a lane map. Current survey techniques are slow and require road closure. There are also issues with how long a road frame can be without adding error to the system. A road frame that is too long in a turn will cause error. The surveyed section of road used for the paper is split into road coordinate frames with an average length of around 10 m.

@inproceedings{lashley_vector_2009,
	title = {Vector {Delay}/{Frequency} {Lock} {Loop} {Implementation} and {Analysis}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=8394},
	abstract = {This paper deals with the advantages in thermal noise performance of vector-based GPS tracking algorithms over traditional receiver architectures. The concept and operation of two different vector tracking algorithms are explained. Specifically, the Vector Delay Lock Loop (VDLL) and Vector Delay/Frequency Lock Loop (VDFLL) are discussed. The similarities between vector tracking loops and scalar tracking loops are discussed. The reasons why vector tracking loops perform better than scalar tracking loops is also covered. The thermal noise performance of the VDLL and VDFLL is analyzed using rule of thumb tracking thresholds. A covariance analysis is used to predict the lowest Carrier to Noise power density ratio (C/N0) at which the vector tracking algorithms can operate. The results of the covariance analysis are verified through Monte Carlo simulations of the vector tracking algorithms. Overall, the results of the analysis match well with the Monte Carlo simulation results.},
	language = {en},
	urldate = {2024-06-20},
	author = {Lashley, Matthew and Bevly, David M.},
	month = jan,
	year = {2009},
	pages = {1073--1086},
}

This paper deals with the advantages in thermal noise performance of vector-based GPS tracking algorithms over traditional receiver architectures. The concept and operation of two different vector tracking algorithms are explained. Specifically, the Vector Delay Lock Loop (VDLL) and Vector Delay/Frequency Lock Loop (VDFLL) are discussed. The similarities between vector tracking loops and scalar tracking loops are discussed. The reasons why vector tracking loops perform better than scalar tracking loops is also covered. The thermal noise performance of the VDLL and VDFLL is analyzed using rule of thumb tracking thresholds. A covariance analysis is used to predict the lowest Carrier to Noise power density ratio (C/N0) at which the vector tracking algorithms can operate. The results of the covariance analysis are verified through Monte Carlo simulations of the vector tracking algorithms. Overall, the results of the analysis match well with the Monte Carlo simulation results.

@article{lashley_performance_2009,
	title = {Performance {Analysis} of {Vector} {Tracking} {Algorithms} for {Weak} {GPS} {Signals} in {High} {Dynamics}},
	volume = {3},
	issn = {1941-0484},
	url = {https://ieeexplore.ieee.org/abstract/document/5166626},
	doi = {10.1109/JSTSP.2009.2023341},
	abstract = {This paper explores the ability of vector tracking algorithms to track weak Global Positioning System (GPS) signals in high dynamic environments. Traditional GPS receivers use tracking loops to track the GPS signals. The signals from each satellite are processed independently. In contrast, vector-based methods do not use tracking loops. Instead, all the satellite signals are tracked by a lone Kalman filter. The Kalman filter combines the tasks of signal tracking and navigation into a single algorithm. Vector-based methods can perform better than traditional methods in environments with high dynamics and low signal power. A performance analysis of the vector tracking algorithms is included. The ability of the algorithms to operate as a function of carrier to noise power density ratio, user dynamics, and number of satellites being used is explored. The vector tracking methods are demonstrated using data from a high fidelity GPS simulator. The simulation results show the vector tracking algorithms operating at a carrier to noise power density ratio of 19 dB-Hz through 2 G, 4 G, and 8 G coordinated turns. The vector tracking algorithms are also shown operating through 2 G and 4 G turns at a carrier to noise power density ratio of 16 dB-Hz.},
	number = {4},
	urldate = {2024-06-20},
	journal = {IEEE Journal of Selected Topics in Signal Processing},
	author = {Lashley, Matthew and Bevly, David M. and Hung, John Y.},
	month = aug,
	year = {2009},
	keywords = {Delay lock loop, Global Positioning System, Global Positioning System (GPS), Kalman filter, Performance analysis, Satellite broadcasting, Satellite navigation systems, Signal processing, Signal processing algorithms, Signal to noise ratio, Tracking loops, Vehicle dynamics, Working environment noise, frequency lock loop, vector tracking},
	pages = {661--673},
}

This paper explores the ability of vector tracking algorithms to track weak Global Positioning System (GPS) signals in high dynamic environments. Traditional GPS receivers use tracking loops to track the GPS signals. The signals from each satellite are processed independently. In contrast, vector-based methods do not use tracking loops. Instead, all the satellite signals are tracked by a lone Kalman filter. The Kalman filter combines the tasks of signal tracking and navigation into a single algorithm. Vector-based methods can perform better than traditional methods in environments with high dynamics and low signal power. A performance analysis of the vector tracking algorithms is included. The ability of the algorithms to operate as a function of carrier to noise power density ratio, user dynamics, and number of satellites being used is explored. The vector tracking methods are demonstrated using data from a high fidelity GPS simulator. The simulation results show the vector tracking algorithms operating at a carrier to noise power density ratio of 19 dB-Hz through 2 G, 4 G, and 8 G coordinated turns. The vector tracking algorithms are also shown operating through 2 G and 4 G turns at a carrier to noise power density ratio of 16 dB-Hz.

@inproceedings{edwards_fpga_2009,
	title = {{FPGA} {Implementation} of a {Vector} {Tracking} {GPS} {Receiver} using {Model}-{Based} {Tools}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=8430},
	abstract = {This paper seeks to introduce the reader to field-programmable gate arrays (FPGAs), vector tracking GNSS algorithms, and to discuss the implementation details of a real-time vector tracking platform on an FPGA. In the navigation community, researchers have utilized the FPGA as a realtime platform for the implementation of GPS receiver algorithms [1–3]. Researchers have also separately analyzed the efficacy of vector tracking algorithms [4–7]. Real-time vector tracking systems have been previously designed, but there are no documented attempts of achieving real-time performance using an FPGA. A traditional receiver architecture uses scalar tracking loops that operate independently in order to estimate the parameters of received satellite signals. In a vector based architecture, these scalar tracking loops are replaced by an extended Kalman filter (EKF) which tracks received signals and estimates the receiver’s position, velocity, and time states simultaneously. Some of the advantages of using vector tracking algorithms include increased interference and jamming immunity and the ability to function in very low signal to noise ratios. These advantages come, however, at a significant increase in computational cost and algorithm complexity, which poses an obstacle for a realtime vector tracking solution. An FPGA contains many inherent qualities that make it an ideal platform for achieving this real-time performance. It offers the possibility of high parallelism, speed comparable to an ASIC, a large number of input/output (I/O), reprogrammability, and a great deal of design flexibility. Recently, FPGA vendors have recognized that many of their clients use FPGAs to perform digital signal processing (DSP) and have therefore created software suites especially suited for DSP applications. These model-based tools are part of the integral framework for implementing the vector tracking algorithms at a significantly reduced development time. This paper discusses an actual vector tracking system that is currently in development using these model-based DSP tools where some of the methods in which the difficulties of vector tracking have been mitigated.},
	language = {en},
	urldate = {2024-06-20},
	author = {Edwards, W. L. and Lashley, M. and Bevly, D. M.},
	month = sep,
	year = {2009},
	pages = {273--280},
}

This paper seeks to introduce the reader to field-programmable gate arrays (FPGAs), vector tracking GNSS algorithms, and to discuss the implementation details of a real-time vector tracking platform on an FPGA. In the navigation community, researchers have utilized the FPGA as a realtime platform for the implementation of GPS receiver algorithms [1–3]. Researchers have also separately analyzed the efficacy of vector tracking algorithms [4–7]. Real-time vector tracking systems have been previously designed, but there are no documented attempts of achieving real-time performance using an FPGA. A traditional receiver architecture uses scalar tracking loops that operate independently in order to estimate the parameters of received satellite signals. In a vector based architecture, these scalar tracking loops are replaced by an extended Kalman filter (EKF) which tracks received signals and estimates the receiver’s position, velocity, and time states simultaneously. Some of the advantages of using vector tracking algorithms include increased interference and jamming immunity and the ability to function in very low signal to noise ratios. These advantages come, however, at a significant increase in computational cost and algorithm complexity, which poses an obstacle for a realtime vector tracking solution. An FPGA contains many inherent qualities that make it an ideal platform for achieving this real-time performance. It offers the possibility of high parallelism, speed comparable to an ASIC, a large number of input/output (I/O), reprogrammability, and a great deal of design flexibility. Recently, FPGA vendors have recognized that many of their clients use FPGAs to perform digital signal processing (DSP) and have therefore created software suites especially suited for DSP applications. These model-based tools are part of the integral framework for implementing the vector tracking algorithms at a significantly reduced development time. This paper discusses an actual vector tracking system that is currently in development using these model-based DSP tools where some of the methods in which the difficulties of vector tracking have been mitigated.

@unpublished{henderson_relative_2008,
	type = {Thesis},
	title = {Relative {Positioning} of {Unmanned} {Ground} {Vehicles} {Using} {Ultrasonic} {Sensors}},
	url = {https://etd.auburn.edu//handle/10415/9},
	abstract = {In this thesis, a Global Positioning System/Inertial Navigation System (GPS/INS) is developed and applied to a tracked Unmanned Ground Vehicle (UGV) to provide estimates of position, heading, and velocity.  The navigation estimator is then augmented with ultrasonic sensors to accurately determine the relative position of a pair of tracked UGVs.  The estimator provides estimates on critical system parameters to allow for automation or collaboration.  The capabilities of UGVs can be greatly increased through automation and collaboration of multiple UGVs.  Automation reduces the operator workload and allows the UGV to continue operations during a loss of communication.  Collaboration allows multiple small UGVs to accomplish tasks previously requiring a single large UGV. A microcontroller uses the ultra-precise Pulse Per Second (PPS) from the GPS to trigger the ultrasonic sensors.  This configuration minimizes the problems traditionally encountered with use of ultrasonic sensors in an outdoor environment while providing additional information to the navigation estimator.  Small, low cost sensors using MEMS technology are employed to minimize size and cost, providing a solution that can be implemented on current UGVs.  Experimental results are presented to compare the performance using GPS alone, GPS/INS, and GPS/INS/Ultrasonic sensors for estimating relative positions and headings of multiple UGVs.},
	language = {en\_US},
	urldate = {2024-06-25},
	author = {Henderson, Harold},
	month = may,
	year = {2008},
	note = {Accepted: 2008-09-09T21:12:42Z},
}

In this thesis, a Global Positioning System/Inertial Navigation System (GPS/INS) is developed and applied to a tracked Unmanned Ground Vehicle (UGV) to provide estimates of position, heading, and velocity. The navigation estimator is then augmented with ultrasonic sensors to accurately determine the relative position of a pair of tracked UGVs. The estimator provides estimates on critical system parameters to allow for automation or collaboration. The capabilities of UGVs can be greatly increased through automation and collaboration of multiple UGVs. Automation reduces the operator workload and allows the UGV to continue operations during a loss of communication. Collaboration allows multiple small UGVs to accomplish tasks previously requiring a single large UGV. A microcontroller uses the ultra-precise Pulse Per Second (PPS) from the GPS to trigger the ultrasonic sensors. This configuration minimizes the problems traditionally encountered with use of ultrasonic sensors in an outdoor environment while providing additional information to the navigation estimator. Small, low cost sensors using MEMS technology are employed to minimize size and cost, providing a solution that can be implemented on current UGVs. Experimental results are presented to compare the performance using GPS alone, GPS/INS, and GPS/INS/Ultrasonic sensors for estimating relative positions and headings of multiple UGVs.

@unpublished{edwards_parameter_2008,
	type = {Thesis},
	title = {Parameter {Estimation} {Techniques} for {Determining} {Safe} {Vehicle} {Speeds} in {UGVs}},
	url = {https://etd.auburn.edu//handle/10415/10},
	abstract = {This thesis develops simplified equations to predict a velocity in which vehicle rollover or tire saturation occurs. These equations are functions of different vehicle parameters that are important to vehicle handling characteristics. Therefore, various algorithms are developed to estimate parameters such as vehicle tire stiffness, peak tire force, and center of gravity position on-line. A number of vehicle control systems have been developed in order to reduce rollover and help maintain vehicle stability. However, many of these control systems do not take into account changing vehicle parameters. Therefore using the on-line estimates of these parameters, the control systems could be more effective in decreasing the number of vehicle accidents. 
    The thesis first explains the fundamentals of lateral vehicle dynamics. Basic vehicle dynamic models are derived and validated to show the effectiveness and shortcomings of the different models. Many assumptions are used to simplify the models. The assumptions leads to simplified equations that predict a velocity in which vehicle rollover or tire saturation occur. An equation to predict the vehicle stopping distance is also derived. Experiments are run to control the vehicle speed to the predictive velocity. This velocity is updated with the identified parameters from the estimation algorithms. By providing the updated velocity to the steering controller, a vehicle is able to transverse a maneuver at a safe speed.},
	language = {en\_US},
	urldate = {2024-06-20},
	author = {Edwards, Dustin},
	month = may,
	year = {2008},
}

This thesis develops simplified equations to predict a velocity in which vehicle rollover or tire saturation occurs. These equations are functions of different vehicle parameters that are important to vehicle handling characteristics. Therefore, various algorithms are developed to estimate parameters such as vehicle tire stiffness, peak tire force, and center of gravity position on-line. A number of vehicle control systems have been developed in order to reduce rollover and help maintain vehicle stability. However, many of these control systems do not take into account changing vehicle parameters. Therefore using the on-line estimates of these parameters, the control systems could be more effective in decreasing the number of vehicle accidents. The thesis first explains the fundamentals of lateral vehicle dynamics. Basic vehicle dynamic models are derived and validated to show the effectiveness and shortcomings of the different models. Many assumptions are used to simplify the models. The assumptions leads to simplified equations that predict a velocity in which vehicle rollover or tire saturation occur. An equation to predict the vehicle stopping distance is also derived. Experiments are run to control the vehicle speed to the predictive velocity. This velocity is updated with the identified parameters from the estimation algorithms. By providing the updated velocity to the steering controller, a vehicle is able to transverse a maneuver at a safe speed.

@unpublished{derrick_adaptive_2008,
	type = {Thesis},
	title = {Adaptive {Control} of a {Farm} {Tractor} with {Varying} {Yaw} {Properties} {Accounting} for {Actuator} {Dynamics} and {Nonlinearities}},
	url = {https://etd.auburn.edu//handle/10415/6},
	abstract = {Two adaptive control algorithms for the automatic steering control of a farm tractor with varying hitch forces are developed.  Tractors can be configured many different implements, and implements interact with the soil in various ways.  These variations cause the yaw dynamics to change with respect to different implements and soil conditions; therefore, this thesis uses a model reference adaptive (MRAC) control law to compensate for different implement configurations.  Models are described and analyzed for the steering actuator, yaw rate plant, and lateral position plant.  It is shown that the DC gain of the steering angle to yaw rate transfer function is the model parameter that changes the most with hitch loading.  In order to develop the adaptive control algorithm, a cascaded controller is first implemented with three feedback loops containing the steering angle, yaw rate, and lateral position measurements.  Controllers are designed for each subsystem, and root locus analysis is used to describe the stability and performance characteristics.  

Two MRAC algorithms are derived to compensate the loop gain and feed-forward gain of the yaw rate controller to account for changes in the yaw rate plant.  The two algorithms are named the model reference adaptive control loop gain adaptation (MRAC-LGA) algorithm and the model reference adaptive control feed-forward gain adaptation (MRAC-FGA) algorithm.  Simulations are presented that show that the algorithms perform poorly due to neglected steering actuator properties.  Both algorithms are modified to account for the steering actuator properties, and more simulations are presented that demonstrate satisfactory performance.  Experimental results are presented for the LGA algorithm, and issues with experimental implementation are discussed.  Next, experimental results are presented for the FGA algorithm that show improved performance over the LGA algorithm.  Finally, experimental tests further validate that the FGA algorithm improves lateral error performance versus a fixed-gain controller.},
	language = {en\_US},
	urldate = {2024-06-25},
	author = {Derrick, John},
	month = may,
	year = {2008},
	note = {Accepted: 2008-09-09T21:12:37Z},
}

Two adaptive control algorithms for the automatic steering control of a farm tractor with varying hitch forces are developed. Tractors can be configured many different implements, and implements interact with the soil in various ways. These variations cause the yaw dynamics to change with respect to different implements and soil conditions; therefore, this thesis uses a model reference adaptive (MRAC) control law to compensate for different implement configurations. Models are described and analyzed for the steering actuator, yaw rate plant, and lateral position plant. It is shown that the DC gain of the steering angle to yaw rate transfer function is the model parameter that changes the most with hitch loading. In order to develop the adaptive control algorithm, a cascaded controller is first implemented with three feedback loops containing the steering angle, yaw rate, and lateral position measurements. Controllers are designed for each subsystem, and root locus analysis is used to describe the stability and performance characteristics. Two MRAC algorithms are derived to compensate the loop gain and feed-forward gain of the yaw rate controller to account for changes in the yaw rate plant. The two algorithms are named the model reference adaptive control loop gain adaptation (MRAC-LGA) algorithm and the model reference adaptive control feed-forward gain adaptation (MRAC-FGA) algorithm. Simulations are presented that show that the algorithms perform poorly due to neglected steering actuator properties. Both algorithms are modified to account for the steering actuator properties, and more simulations are presented that demonstrate satisfactory performance. Experimental results are presented for the LGA algorithm, and issues with experimental implementation are discussed. Next, experimental results are presented for the FGA algorithm that show improved performance over the LGA algorithm. Finally, experimental tests further validate that the FGA algorithm improves lateral error performance versus a fixed-gain controller.

@unpublished{clark_gpsins_2008,
	type = {Thesis},
	title = {{GPS}/{INS} {Operation} in {Shadowed} {Environments}},
	url = {https://etd.auburn.edu//handle/10415/1223},
	abstract = {This thesis presents the analysis techniques developed for monitoring GPS signals in harsh shadowed environments such as heavy foliage.  It also details a method selected for improved performance by combining raw GPS information with an Inertial Navigation System (INS).  Normal GPS operation in shadowed areas suffer from position jumps of tens to hundreds of meters.  The developed analysis reveals that these errors are due to the quickly changing local errors that cause a GPS receiver to report erroneous position spikes.  Monitoring variables for the signal strength and change in multipath are employed to keep track of the environmental effects on the GPS measurements.  A new visualization technique is also developed to qualitatively monitor the environmental effects.

From the visualization technique, the effects of the shadowing environment are shown to simultaneously affect the signal strength and multipath.  It is shown that foliage cover causes these effects to occur spontaneously as a signal travels through and around obstacles.  To mitigate these errors, a GPS/INS closely coupled system is implemented which uses inertial sensors to smooth the erroneous GPS jumps.  Introduction of alternative sensors allows for integrity monitoring in the form of GPS outlier measurement rejection so that local environmental effects can be detected and removed from the navigation solution.  The resulting implementation reveals that it is possible to operate in these GPS harsh environments without suffering from the position jumps of tens or hundreds of meters.  This implementation allows for navigation in foliage cover comparable to the under ten meter accuracy of standard GPS in clear environments.},
	language = {en\_US},
	urldate = {2024-06-25},
	author = {Clark, Benjamin},
	month = aug,
	year = {2008},
	note = {Accepted: 2008-09-09T22:37:33Z},
}

This thesis presents the analysis techniques developed for monitoring GPS signals in harsh shadowed environments such as heavy foliage. It also details a method selected for improved performance by combining raw GPS information with an Inertial Navigation System (INS). Normal GPS operation in shadowed areas suffer from position jumps of tens to hundreds of meters. The developed analysis reveals that these errors are due to the quickly changing local errors that cause a GPS receiver to report erroneous position spikes. Monitoring variables for the signal strength and change in multipath are employed to keep track of the environmental effects on the GPS measurements. A new visualization technique is also developed to qualitatively monitor the environmental effects. From the visualization technique, the effects of the shadowing environment are shown to simultaneously affect the signal strength and multipath. It is shown that foliage cover causes these effects to occur spontaneously as a signal travels through and around obstacles. To mitigate these errors, a GPS/INS closely coupled system is implemented which uses inertial sensors to smooth the erroneous GPS jumps. Introduction of alternative sensors allows for integrity monitoring in the form of GPS outlier measurement rejection so that local environmental effects can be detected and removed from the navigation solution. The resulting implementation reveals that it is possible to operate in these GPS harsh environments without suffering from the position jumps of tens or hundreds of meters. This implementation allows for navigation in foliage cover comparable to the under ten meter accuracy of standard GPS in clear environments.

@unpublished{daily_stream_2008,
	title = {Stream {Function} {Path} {Planning} and {Control} for {Unmanned} {Ground} {Vehicles}},
	url = {https://etd.auburn.edu//handle/10415/1222},
	abstract = {This research develops a harmonic potential field based path planner and controller.  The first component of the dissertation compares several analytical and numerical potential field generation methods.  To overcome limitations present in the existing methods, two new methods are developed to meet the specific requirements of this research (generic shape obstacles and an explicit stream function).  In particular, an analytic method to combine circles and create generic shaped obstacles is presented.  Additionally, a numeric technique to directly calculate a potential field stream function is developed.
The second part of this research extends the traditional potential field controller to track a desired streamline as well as the potential field gradient.  In addition to tracking a streamline, the reference path is also modified to maximize safety as the vehicle is driving.  In particular, a separate harmonic potential field is created for the desired speed.  This speed is low near obstacles and high in the open field.  The lateral acceleration of the vehicle is also limited by reducing the steer angle and desired speed whenever an acceleration threshold is crossed.  Finally, to create a buffer between the vehicle and obstacles, whenever the vehicle is close to an obstacle the desired streamline is shifted away from the obstacles.  Together these three real-time modifications to the controller keep the vehicle safely away from obstacles and within its handling limitations.},
	language = {en\_US},
	urldate = {2024-06-25},
	author = {Daily, Robert},
	month = aug,
	year = {2008},
	note = {Accepted: 2008-09-09T22:37:32Z},
}

This research develops a harmonic potential field based path planner and controller. The first component of the dissertation compares several analytical and numerical potential field generation methods. To overcome limitations present in the existing methods, two new methods are developed to meet the specific requirements of this research (generic shape obstacles and an explicit stream function). In particular, an analytic method to combine circles and create generic shaped obstacles is presented. Additionally, a numeric technique to directly calculate a potential field stream function is developed. The second part of this research extends the traditional potential field controller to track a desired streamline as well as the potential field gradient. In addition to tracking a streamline, the reference path is also modified to maximize safety as the vehicle is driving. In particular, a separate harmonic potential field is created for the desired speed. This speed is low near obstacles and high in the open field. The lateral acceleration of the vehicle is also limited by reducing the steer angle and desired speed whenever an acceleration threshold is crossed. Finally, to create a buffer between the vehicle and obstacles, whenever the vehicle is close to an obstacle the desired streamline is shifted away from the obstacles. Together these three real-time modifications to the controller keep the vehicle safely away from obstacles and within its handling limitations.

@inproceedings{clark_gpsins_2008,
	title = {{GPS}/{INS} integration with fault detection and exclusion in shadowed environments},
	url = {https://ieeexplore.ieee.org/document/4569963/;jsessionid=EF64BFBA03753F2FA78108DC0D28E974},
	doi = {10.1109/PLANS.2008.4569963},
	abstract = {This paper presents a method for GPS/INS operation in shadowed environments such as urban canyons and rural foliage cover. Shadowing causes a combination of multipath and signal attenuation which results in increased uncertainty in the GPS observables and sometimes complete loss of satellite tracking. Environment layout and the line-of-sight vector to the affected satellite determines the degree of shadowing in the range domain. Details are provided for the failure modes and effects in such environments. These results are used in the analysis of a fault detection and exclusion (FDE) algorithm to provide integrity to the GPS observables.},
	urldate = {2024-06-20},
	booktitle = {2008 {IEEE}/{ION} {Position}, {Location} and {Navigation} {Symposium}},
	author = {Clark, Benjamin J. and Bevly, David M.},
	month = may,
	year = {2008},
	note = {ISSN: 2153-3598},
	keywords = {Attenuation, Automotive engineering, Degradation, Educational institutions, Fault detection, Global Positioning System, Monitoring, Satellite navigation systems, Shadow mapping, Vehicle dynamics},
	pages = {1--8},
}

This paper presents a method for GPS/INS operation in shadowed environments such as urban canyons and rural foliage cover. Shadowing causes a combination of multipath and signal attenuation which results in increased uncertainty in the GPS observables and sometimes complete loss of satellite tracking. Environment layout and the line-of-sight vector to the affected satellite determines the degree of shadowing in the range domain. Details are provided for the failure modes and effects in such environments. These results are used in the analysis of a fault detection and exclusion (FDE) algorithm to provide integrity to the GPS observables.

@inproceedings{derrick_model-reference_2008,
	title = {Model-reference adaptive steering control of a farm tractor with varying hitch forces},
	url = {https://ieeexplore.ieee.org/document/4587065/;jsessionid=868201FA3839C3919502A203F02EAEF6},
	doi = {10.1109/ACC.2008.4587065},
	abstract = {This paper presents a model-reference adaptive controller (MRAC) for steering a farm tractor with varying hitch forces. Hitch forces play an important role in the yaw dynamics of the tractor, and these forces change with respect to different implements and soil conditions. It is desired that the tractor has the same dynamic response no matter what the hitch forces may be. A good dynamic yaw model has been developed for a tractor with hitch forces, and one parameter in this model changes with hitch loading. A MRAC algorithm is consequently proposed to directly adapt one controller parameter to changing hitch loading. A set of cascaded controllers will be used to regulate the tractor's lateral position, although only the controller that directly regulates the yaw rate will be adapted. The adaptation algorithm is then augmented to account for inner-loop steering actuator dynamics and saturations. Simulated and experimental results are presented.},
	urldate = {2024-06-20},
	booktitle = {2008 {American} {Control} {Conference}},
	author = {Derrick, J. Benton and Bevly, David M. and Rekow, Andrew K.},
	month = jun,
	year = {2008},
	note = {ISSN: 2378-5861},
	keywords = {Actuators, Adaptive control, Agricultural machinery, Control systems, Force control, Global Positioning System, Land vehicles, Programmable control, Soil, Vehicle dynamics},
	pages = {3677--3682},
}

This paper presents a model-reference adaptive controller (MRAC) for steering a farm tractor with varying hitch forces. Hitch forces play an important role in the yaw dynamics of the tractor, and these forces change with respect to different implements and soil conditions. It is desired that the tractor has the same dynamic response no matter what the hitch forces may be. A good dynamic yaw model has been developed for a tractor with hitch forces, and one parameter in this model changes with hitch loading. A MRAC algorithm is consequently proposed to directly adapt one controller parameter to changing hitch loading. A set of cascaded controllers will be used to regulate the tractor's lateral position, although only the controller that directly regulates the yaw rate will be adapted. The adaptation algorithm is then augmented to account for inner-loop steering actuator dynamics and saturations. Simulated and experimental results are presented.

@inproceedings{britt_automated_2008,
	title = {Automated modeling of the guidance of a {K}-9},
	url = {https://ieeexplore.ieee.org/document/4586861/;jsessionid=82D5EBD9912D34052FDAA7827283D4D0},
	doi = {10.1109/ACC.2008.4586861},
	abstract = {This paper attempts to automate and replace human guidance in the control of a K-9 unit by modeling that guidance from observation. The ultimate research goal seeks to contribute toward the autonomous command of a trained K-9 unit by analyzing the movement and the behavior of the dog as it responds to command tones. Specifically, GPS and command signal information (from a human trainer) is recorded as a canine follows (or fails to follow) instructions as it moves toward a destination. The data is then processed into training instances and used as training data for a general regression neural network (GRNN). Then, the network is used to classify previously unseen test instances to determine if the behavior at that moment is normal or anomalous (in need of correcting tones). Both representation of training instances and the system parameters of the GRNN are optimized using a simple evolutionary hill-climber (EHC). Given even fairly limited initial data for training, the system performs well, producing relatively few false positives and false negatives in classification.},
	urldate = {2024-06-20},
	booktitle = {2008 {American} {Control} {Conference}},
	author = {Britt, Winard and Bevly, David M. and Dozier, Gerry},
	month = jun,
	year = {2008},
	note = {ISSN: 2378-5861},
	keywords = {Automatic control, Computer science, Data security, Global Positioning System, Humans, Intelligent robots, Intelligent sensors, Neural networks, Testing, Training data},
	pages = {2467--2474},
}

This paper attempts to automate and replace human guidance in the control of a K-9 unit by modeling that guidance from observation. The ultimate research goal seeks to contribute toward the autonomous command of a trained K-9 unit by analyzing the movement and the behavior of the dog as it responds to command tones. Specifically, GPS and command signal information (from a human trainer) is recorded as a canine follows (or fails to follow) instructions as it moves toward a destination. The data is then processed into training instances and used as training data for a general regression neural network (GRNN). Then, the network is used to classify previously unseen test instances to determine if the behavior at that moment is normal or anomalous (in need of correcting tones). Both representation of training instances and the system parameters of the GRNN are optimized using a simple evolutionary hill-climber (EHC). Given even fairly limited initial data for training, the system performs well, producing relatively few false positives and false negatives in classification.

@inproceedings{daily_harmonic_2008,
	title = {Harmonic potential field path planning for high speed vehicles},
	url = {https://ieeexplore.ieee.org/document/4587222/;jsessionid=9C8F3B0BFE035050A426F0CA83919525},
	doi = {10.1109/ACC.2008.4587222},
	abstract = {This paper presents a method to represent complex shaped obstacles in harmonic potential fields used for vehicle path planning. The proposed method involves calculating the potential field for a series of circular obstacles inserted into the unobstructed potential field. The potential field for the total obstacle is a weighted average of the circular obstacle potential fields. This method explicitly calculates a stream function for the potential field. The need for the stream function is explained for situations involving controlling a dynamic system such as a high speed ground vehicle. The traditional potential field controller is also augmented to take the stream function into account. Simulation results are presented to show the effectiveness of the potential field generation technique and the augmented vehicle controller.},
	urldate = {2024-06-20},
	booktitle = {2008 {American} {Control} {Conference}},
	author = {Daily, Robert and Bevly, David M.},
	month = jun,
	year = {2008},
	note = {ISSN: 2378-5861},
	keywords = {Aerodynamics, Boundary conditions, Control systems, Land vehicles, Laplace equations, Mobile robots, Path planning, Robot control, Vehicle dynamics, Velocity control},
	pages = {4609--4614},
}

This paper presents a method to represent complex shaped obstacles in harmonic potential fields used for vehicle path planning. The proposed method involves calculating the potential field for a series of circular obstacles inserted into the unobstructed potential field. The potential field for the total obstacle is a weighted average of the circular obstacle potential fields. This method explicitly calculates a stream function for the potential field. The need for the stream function is explained for situations involving controlling a dynamic system such as a high speed ground vehicle. The traditional potential field controller is also augmented to take the stream function into account. Simulation results are presented to show the effectiveness of the potential field generation technique and the augmented vehicle controller.

@inproceedings{travis_trajectory_2008,
	title = {Trajectory duplication using relative position information for automated ground vehicle convoys},
	url = {https://ieeexplore.ieee.org/document/4570076/;jsessionid=917182AFC14A26DF23FFA9B663301A08},
	doi = {10.1109/PLANS.2008.4570076},
	abstract = {A strategy to enhance the accuracy of path following for autonomous ground vehicles in a convoy is presented. GPS carrier measurements are used to estimate relative position with sub-two centimeter accuracy and a change in position to millimeter accuracy. These estimates are used in conjunction with three methods presented that enable a following vehicle to replicate a lead vehiclepsilas path of travel while both are in motion and not in sight of one another. Accuracies of the methods achieved in simulation are shown with discussion on the benefits and shortcomings of each method. Simulation results show a 1.6 meter error at a 50 m following distance. Discussion explains the inaccuracies are due to the limitations inherent in the selected vehicle controller and not necessarily in the trajectory duplication methods.},
	urldate = {2024-06-20},
	booktitle = {2008 {IEEE}/{ION} {Position}, {Location} and {Navigation} {Symposium}},
	author = {Travis, William and Bevly, David M.},
	month = may,
	year = {2008},
	note = {ISSN: 2153-3598},
	keywords = {Automotive engineering, Educational institutions, Global Positioning System, Land vehicles, Motion estimation, Position measurement, Remotely operated vehicles, Vehicle driving, Vehicle dynamics, Vehicle safety},
	pages = {1022--1032},
}

A strategy to enhance the accuracy of path following for autonomous ground vehicles in a convoy is presented. GPS carrier measurements are used to estimate relative position with sub-two centimeter accuracy and a change in position to millimeter accuracy. These estimates are used in conjunction with three methods presented that enable a following vehicle to replicate a lead vehiclepsilas path of travel while both are in motion and not in sight of one another. Accuracies of the methods achieved in simulation are shown with discussion on the benefits and shortcomings of each method. Simulation results show a 1.6 meter error at a 50 m following distance. Discussion explains the inaccuracies are due to the limitations inherent in the selected vehicle controller and not necessarily in the trajectory duplication methods.

@inproceedings{lashley_impact_2008,
	title = {Impact of carrier to noise power density, platform dynamics, and {IMU} quality on deeply integrated navigation},
	url = {https://ieeexplore.ieee.org/document/4569964/;jsessionid=03CC9F9CB4420EF21DCCC8E113AA1A79},
	doi = {10.1109/PLANS.2008.4569964},
	abstract = {In this paper, the authors investigate how the Carrier to Noise power density ratio (C/N0), platform dynamics, and differing Inertial Measurement Unit (IMU) quality affect the performance of Deeply Integrated (DI) algorithms. Two different DI algorithms are described in detail and analyzed using a high fidelity GPS simulator. The first algorithm is a Vector Delay/Frequency Lock Loop (VDFLL). The second algorithm is a Deeply Integrated GPS/INS system with differing grades of IMUpsilas. The ability of the algorithms to operate at low C/N0 levels and in high dynamics is investigated empirically with the GPS simulator. The VDFLL algorithm can successfully track the received GPS signals through 2 g, 4 g, and 8 g coordinated turns at 19 dB-Hz. Initial results of the Deeply Integrated GPS/INS algorithm show its operation through the 2 g, 4 g, and 8 g coordinated turn at 16 dB-Hz with a tactical grade IMU.},
	urldate = {2024-06-20},
	booktitle = {2008 {IEEE}/{ION} {Position}, {Location} and {Navigation} {Symposium}},
	author = {Lashley, Matthew and Bevly, David M. and Hung, John Y.},
	month = may,
	year = {2008},
	note = {ISSN: 2153-3598},
	keywords = {Correlators, Filters, Frequency locked loops, Frequency measurement, Global Positioning System, Phase estimation, Satellite navigation systems, State estimation, Tracking loops, Vehicle dynamics},
	pages = {9--16},
}

In this paper, the authors investigate how the Carrier to Noise power density ratio (C/N0), platform dynamics, and differing Inertial Measurement Unit (IMU) quality affect the performance of Deeply Integrated (DI) algorithms. Two different DI algorithms are described in detail and analyzed using a high fidelity GPS simulator. The first algorithm is a Vector Delay/Frequency Lock Loop (VDFLL). The second algorithm is a Deeply Integrated GPS/INS system with differing grades of IMUpsilas. The ability of the algorithms to operate at low C/N0 levels and in high dynamics is investigated empirically with the GPS simulator. The VDFLL algorithm can successfully track the received GPS signals through 2 g, 4 g, and 8 g coordinated turns at 19 dB-Hz. Initial results of the Deeply Integrated GPS/INS algorithm show its operation through the 2 g, 4 g, and 8 g coordinated turn at 16 dB-Hz with a tactical grade IMU.

@inproceedings{travis_ugv_2008,
	address = {Honolulu, Hawaii},
	title = {{UGV} {Trailer} {Position} {Estimation} {Using} a {Dynamic} {Base} {RTK} {System}},
	isbn = {978-1-60086-999-0},
	url = {https://arc.aiaa.org/doi/10.2514/6.2008-7442},
	doi = {10.2514/6.2008-7442},
	language = {en},
	urldate = {2024-06-20},
	booktitle = {{AIAA} {Guidance}, {Navigation} and {Control} {Conference} and {Exhibit}},
	publisher = {American Institute of Aeronautics and Astronautics},
	author = {Travis, William and Hodo, David and Bevly, David and Hung, John},
	month = aug,
	year = {2008},
}

@inproceedings{lashley_comparison_2008,
	address = {Honolulu, Hawaii},
	title = {Comparison of {Adaptive} {Estimation} {Techniques} for {Vector} {Delay}/{Frequency} {Tracking}},
	isbn = {978-1-60086-999-0},
	url = {https://arc.aiaa.org/doi/10.2514/6.2008-7474},
	doi = {10.2514/6.2008-7474},
	language = {en},
	urldate = {2024-06-20},
	booktitle = {{AIAA} {Guidance}, {Navigation} and {Control} {Conference} and {Exhibit}},
	publisher = {American Institute of Aeronautics and Astronautics},
	author = {Lashley, Matthew and Bevly, David},
	month = aug,
	year = {2008},
}

@inproceedings{nevin_object_2008,
	title = {Object {Registration} through {Statistics} and {Hough} {Transform}},
	url = {https://www.actapress.com/Abstract.aspx?paperId=34400},
	abstract = {We investigate different methods to detect objects in asequence of images with digital image processing techniques, and propose a registration method that combineslocal statistics with gradients to identify and track objectsfrom frame to frame.},
	urldate = {2024-06-20},
	publisher = {ACTA Press},
	author = {Nevin, A. and Hodel, A. S. and Bevly, D. M.},
	month = oct,
	year = {2008},
}

We investigate different methods to detect objects in asequence of images with digital image processing techniques, and propose a registration method that combineslocal statistics with gradients to identify and track objectsfrom frame to frame.

@inproceedings{huang_using_2008,
	title = {Using {3D} road geometry to optimize heavy truck fuel efficiency},
	url = {https://ieeexplore.ieee.org/abstract/document/4732656},
	doi = {10.1109/ITSC.2008.4732656},
	abstract = {This paper investigates the benefit of using a 3D road geometry based optimal powertrain control system in reducing the fuel consumption of heavy trucks. The optimal control system, using constrained nonlinear programming, is designed to predict the optimal throttle, gear shifting and velocity trajectory, to minimize the fuel consumption and travel time. Computer simulations of a Class 8 truck model are conducted with Intermap 3D road geometry. Simulation results show that the optimal control system is able to reduce the fuel consumption with equal travel time, when compared to the defined baseline. Additionally, sensitivity analyses are conducted to investigate how the change of the terrain and the errors in the road map affect the gain of fuel economy and system behavior.},
	urldate = {2024-06-20},
	booktitle = {2008 11th {International} {IEEE} {Conference} on {Intelligent} {Transportation} {Systems}},
	author = {Huang, Wei and Bevly, David M. and Schnick, Steve and Li, Xiaopeng},
	month = oct,
	year = {2008},
	note = {ISSN: 2153-0017},
	keywords = {Computer simulation, Control systems, Fuels, Gears, Geometry, Mechanical power transmission, Optimal control, Roads, Solid modeling, Trajectory},
	pages = {334--339},
}

This paper investigates the benefit of using a 3D road geometry based optimal powertrain control system in reducing the fuel consumption of heavy trucks. The optimal control system, using constrained nonlinear programming, is designed to predict the optimal throttle, gear shifting and velocity trajectory, to minimize the fuel consumption and travel time. Computer simulations of a Class 8 truck model are conducted with Intermap 3D road geometry. Simulation results show that the optimal control system is able to reduce the fuel consumption with equal travel time, when compared to the defined baseline. Additionally, sensitivity analyses are conducted to investigate how the change of the terrain and the errors in the road map affect the gain of fuel economy and system behavior.

@inproceedings{henderson_relative_2008,
	title = {Relative position of {UGVs} in constrained environments using low cost {IMU} and {GPS} augmented with ultrasonic sensors},
	url = {https://ieeexplore.ieee.org/abstract/document/4570080},
	doi = {10.1109/PLANS.2008.4570080},
	abstract = {This paper presents a low cost approach to improve the relative position accuracy of unmanned ground vehicles (UGV) in a constrained environment through the use of ultrasonic sensors. A low cost MEMS IMU is integrated with a low cost GPS module to estimate the absolute position of the UGVs using an Extended Kalman Filter. The inherent limitations of GPS and MEMS sensors limit the estimatepsilas utility for determining the relative position of a pair of UGVs in close proximity. The estimator is augmented with range and bearing measurements from the ultrasonic sensors to overcome these limitations. The PPS from the GPS provides a common time to the ultrasonic sensors on each of the UGVs. This approach removes the necessity to differentiate between multiple returns for measuring the distance between UGV. Experiments were performed with a pair of sensors in urban terrain to evaluate the accuracy of the relative position estimate using this method. The results display the accuracy and precision of the relative position achieved. The results are compared with estimates from a pair of navigation estimators to illustrate the performance gains.},
	urldate = {2024-06-20},
	booktitle = {2008 {IEEE}/{ION} {Position}, {Location} and {Navigation} {Symposium}},
	author = {Henderson, Harold P. and Bevly, David M.},
	month = may,
	year = {2008},
	note = {ISSN: 2153-3598},
	keywords = {Acoustic sensors, Costs, Global Positioning System, Humans, Land vehicles, Mechanical sensors, Micromechanical devices, Navigation, Robot sensing systems, Ultrasonic variables measurement},
	pages = {1269--1277},
}

This paper presents a low cost approach to improve the relative position accuracy of unmanned ground vehicles (UGV) in a constrained environment through the use of ultrasonic sensors. A low cost MEMS IMU is integrated with a low cost GPS module to estimate the absolute position of the UGVs using an Extended Kalman Filter. The inherent limitations of GPS and MEMS sensors limit the estimatepsilas utility for determining the relative position of a pair of UGVs in close proximity. The estimator is augmented with range and bearing measurements from the ultrasonic sensors to overcome these limitations. The PPS from the GPS provides a common time to the ultrasonic sensors on each of the UGVs. This approach removes the necessity to differentiate between multiple returns for measuring the distance between UGV. Experiments were performed with a pair of sensors in urban terrain to evaluate the accuracy of the relative position estimate using this method. The results display the accuracy and precision of the relative position achieved. The results are compared with estimates from a pair of navigation estimators to illustrate the performance gains.

@inproceedings{derrick_adaptive_2008,
	title = {Adaptive control of a farm tractor with varying yaw dynamics accounting for actuator dynamics and saturations},
	url = {https://ieeexplore.ieee.org/abstract/document/4629591},
	doi = {10.1109/CCA.2008.4629591},
	abstract = {This paper presents an adaptive control system implemented on an automatically steered farm tractor. The yaw dynamics of the tractor are time varying due to different attached implements and soil conditions; therefore, a model reference adaptive control (MRAC) system is developed to automatically adjust the feed-forward yaw rate controller to changes in the current yaw plant. The MRAC algorithm is next modified from itpsilas original form to account for steering actuator dynamics and nonlinearities. Simulated results are presented that demonstrate the algorithmpsilas performance under ideal conditions. Experimental results are presented that show that the algorithm performs well on a real system with changing yaw dynamics. Finally, experimental results are shown that demonstrate improved tracking performance verses a fixed-gain configuration.},
	urldate = {2024-06-20},
	booktitle = {2008 {IEEE} {International} {Conference} on {Control} {Applications}},
	author = {Derrick, J. Benton and Bevly, David M.},
	month = sep,
	year = {2008},
	note = {ISSN: 1085-1992},
	keywords = {Conferences, Control systems, USA Councils},
	pages = {547--552},
}

This paper presents an adaptive control system implemented on an automatically steered farm tractor. The yaw dynamics of the tractor are time varying due to different attached implements and soil conditions; therefore, a model reference adaptive control (MRAC) system is developed to automatically adjust the feed-forward yaw rate controller to changes in the current yaw plant. The MRAC algorithm is next modified from itpsilas original form to account for steering actuator dynamics and nonlinearities. Simulated results are presented that demonstrate the algorithmpsilas performance under ideal conditions. Experimental results are presented that show that the algorithm performs well on a real system with changing yaw dynamics. Finally, experimental results are shown that demonstrate improved tracking performance verses a fixed-gain configuration.

@inproceedings{lashley_comparison_2008,
	title = {A {Comparison} of the {Performance} of a {Non}-{Coherent} {Deeply} {Integrated} {Navigation} {Algorithm} and a {Tightly} {Coupled} {Navigation} {Algorithm}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=8114},
	abstract = {In this paper, the authors compare the performance of a tightly coupled and a Deeply Integrated (DI) navigation algorithm at low Carrier to Noise power density ratios (C/N0). The purpose of the comparison is to ascertain the relative improvement in tracking ability from the DI architecture. In order to make a valid side by side comparison, the algorithms both use the same discriminator functions, signal amplitude estimation techniques, and noise power estimation techniques. The only major difference between the two algorithms is the manner in which their central Extended Kalman Filters (EKF) are updated with GPS measurements. The two algorithms are evaluated using Monte Carlo simulations in MATLAB. The C/N0 ratio is lowered incrementally in the simulations until each algorithm loses lock. From the simulations, the deeply integrated algorithm is shown to work at approximately 6 dB-Hz lower than the tightly coupled algorithm.},
	language = {en},
	urldate = {2024-06-20},
	author = {Lashley, Matthew and Bevly, David M.},
	month = sep,
	year = {2008},
	pages = {2123--2129},
}

In this paper, the authors compare the performance of a tightly coupled and a Deeply Integrated (DI) navigation algorithm at low Carrier to Noise power density ratios (C/N0). The purpose of the comparison is to ascertain the relative improvement in tracking ability from the DI architecture. In order to make a valid side by side comparison, the algorithms both use the same discriminator functions, signal amplitude estimation techniques, and noise power estimation techniques. The only major difference between the two algorithms is the manner in which their central Extended Kalman Filters (EKF) are updated with GPS measurements. The two algorithms are evaluated using Monte Carlo simulations in MATLAB. The C/N0 ratio is lowered incrementally in the simulations until each algorithm loses lock. From the simulations, the deeply integrated algorithm is shown to work at approximately 6 dB-Hz lower than the tightly coupled algorithm.

@unpublished{pearson_modeling_2007,
	type = {Thesis},
	title = {Modeling and {Validation} of {Hitched} {Loading} {Effects} on {Tractor} {Yaw} {Dynamics}},
	url = {https://etd.auburn.edu//handle/10415/819},
	abstract = {This thesis develops a yaw dynamic model for a farm tractor with a hitched
implement, which can be used to understand the effect of tractor handling characteristics
for design applications as well as for new automated steering control systems. A model is
found in which hitched implement conditions can be accounted for, and an improvement
in yaw rate tracking prediction in both steady state and dynamic conditions is seen vs.
traditional models. This model is termed the “3-wheeled” Front and Hitch Relaxation
Length (“3-wheeled” FHRL) Model. Experimental data from a hitch force dynamometer
are used to validate the way the hitched implement forces are derived in the “3-wheeled”
FHRL Model and to determine if differential hitch forces can be ignored. Steady state
and dynamic chirp data taken for a variety of implements at varying depths and speeds
are used to quantify the variation in the hitch parameter and to find the front and hitch
relaxation length values. Finally, a model which accounts for four-wheel drive forces is
derived, and experiments are taken which provide a preliminary look into the effect of
four-wheel drive traction forces on the yaw dynamics of the tractor.
In comparisons with other traditional models, the “3-wheeled” FHRL Model is
shown to be superior in its steady state yaw rate tracking ability with an RMS error of
.245 deg/s vs. 1.96-2.07 deg/s for other models at a certain depth and also superior in its
dynamic tracking ability with an RMS error of .675 deg/s vs. .748-1.37 deg/s for the
other models. The experimental results from the hitch force dynamometer show that the
implement performs according to the linear tire model and that the moment caused by
differential forces at the hitch can be ignored. The hitch parameter, Cah , ranges from 452-
3385 N/deg for various implements and depths tested in this thesis. The front tire
relaxation length is found to be .37 m and the hitch relaxation length is found to be .4 m.
The four-wheel drive experiments show that using four-wheel drive provided an increase
in yaw rate from 9-21\%, depending on the implement depth and speed.},
	language = {en\_US},
	urldate = {2024-06-25},
	author = {Pearson, Paul},
	month = may,
	year = {2007},
	note = {Accepted: 2008-09-09T21:23:42Z},
}

This thesis develops a yaw dynamic model for a farm tractor with a hitched implement, which can be used to understand the effect of tractor handling characteristics for design applications as well as for new automated steering control systems. A model is found in which hitched implement conditions can be accounted for, and an improvement in yaw rate tracking prediction in both steady state and dynamic conditions is seen vs. traditional models. This model is termed the “3-wheeled” Front and Hitch Relaxation Length (“3-wheeled” FHRL) Model. Experimental data from a hitch force dynamometer are used to validate the way the hitched implement forces are derived in the “3-wheeled” FHRL Model and to determine if differential hitch forces can be ignored. Steady state and dynamic chirp data taken for a variety of implements at varying depths and speeds are used to quantify the variation in the hitch parameter and to find the front and hitch relaxation length values. Finally, a model which accounts for four-wheel drive forces is derived, and experiments are taken which provide a preliminary look into the effect of four-wheel drive traction forces on the yaw dynamics of the tractor. In comparisons with other traditional models, the “3-wheeled” FHRL Model is shown to be superior in its steady state yaw rate tracking ability with an RMS error of .245 deg/s vs. 1.96-2.07 deg/s for other models at a certain depth and also superior in its dynamic tracking ability with an RMS error of .675 deg/s vs. .748-1.37 deg/s for the other models. The experimental results from the hitch force dynamometer show that the implement performs according to the linear tire model and that the moment caused by differential forces at the hitch can be ignored. The hitch parameter, Cah , ranges from 452- 3385 N/deg for various implements and depths tested in this thesis. The front tire relaxation length is found to be .37 m and the hitch relaxation length is found to be .4 m. The four-wheel drive experiments show that using four-wheel drive provided an increase in yaw rate from 9-21%, depending on the implement depth and speed.

@unpublished{lambert_study_2007,
	type = {Thesis},
	title = {A {Study} of {Vehicle} {Properties} {That} {Influence} {Rollover} and {Their} {Effect} on {Electronic} {Stability} {Controllers}},
	url = {https://etd.auburn.edu//handle/10415/112},
	abstract = {In this thesis, the vehicle properties that most influence rollover are investigated, and methods to improve stability are examined. Every year, vehicle rollover is the cause of thousands of fatalities on US highways. Electronic Stability Controllers (ESC) have been proven to reduce the incidence of rollover; however, improvement is still possible and necessary. With the development of a detailed vehicle model that includes roll and individual wheel dynamics, research has been done to investigate the properties that most affect rollover. Using these key vehicle properties, equations are developed to estimate the maximum lateral acceleration and velocity allowed before rollover. With a good knowledge of the stability limits, ESC systems are developed in simulation, and testing is done to investigate how these controllers can be optimized to greater ensure stability during evasive maneuvers. Results prove that stability can be improved and that rollover can be averted with correct execution of ESC limits and outputs.},
	language = {en\_US},
	urldate = {2024-06-20},
	author = {Lambert, Kenneth},
	month = dec,
	year = {2007},
}

In this thesis, the vehicle properties that most influence rollover are investigated, and methods to improve stability are examined. Every year, vehicle rollover is the cause of thousands of fatalities on US highways. Electronic Stability Controllers (ESC) have been proven to reduce the incidence of rollover; however, improvement is still possible and necessary. With the development of a detailed vehicle model that includes roll and individual wheel dynamics, research has been done to investigate the properties that most affect rollover. Using these key vehicle properties, equations are developed to estimate the maximum lateral acceleration and velocity allowed before rollover. With a good knowledge of the stability limits, ESC systems are developed in simulation, and testing is done to investigate how these controllers can be optimized to greater ensure stability during evasive maneuvers. Results prove that stability can be improved and that rollover can be averted with correct execution of ESC limits and outputs.

@unpublished{krueger_investigation_2007,
	type = {Thesis},
	title = {Investigation of {Lateral} {Performance} of an {ATV} {Tire} on {Natural}, {Deformable} {Surfaces}},
	copyright = {EMBARGO\_NOT\_AUBURN},
	url = {https://etd.auburn.edu//handle/10415/1350},
	abstract = {A study is undertaken to discover links between soil-rubber interface strength,
camber, pressure and lateral performance of a front ATV tire. New tire and soil test rigs
are also designed and fabricated for the support of this research. The tire is tested at
various geometries and inflation pressures on cohesive and frictional soils. Lateral,
longitudinal and vertical forces are recorded with an electronic data logging system.
Using the results from the tire tests, an exponential tire model is fit to the tire data.
Coefficients of the model are then compared to the inflation pressures, camber angles,
and soil data. The effects on tire performance trends are observed. Data from these
experiments can be used to aid in the programming of autonomous unmanned ground
vehicles, or to create better vehicle dynamics models for small off-road vehicles.},
	language = {en\_US},
	urldate = {2024-06-25},
	author = {Krueger, Darrell},
	month = dec,
	year = {2007},
	note = {Accepted: 2009-02-23T15:53:02Z},
}

A study is undertaken to discover links between soil-rubber interface strength, camber, pressure and lateral performance of a front ATV tire. New tire and soil test rigs are also designed and fabricated for the support of this research. The tire is tested at various geometries and inflation pressures on cohesive and frictional soils. Lateral, longitudinal and vertical forces are recorded with an electronic data logging system. Using the results from the tire tests, an exponential tire model is fit to the tire data. Coefficients of the model are then compared to the inflation pressures, camber angles, and soil data. The effects on tire performance trends are observed. Data from these experiments can be used to aid in the programming of autonomous unmanned ground vehicles, or to create better vehicle dynamics models for small off-road vehicles.

@unpublished{hodo_development_2007,
	type = {Thesis},
	title = {Development of an {Autonomous} {Mobile} {Robot}-{Trailer} {System} for {UXO} {Detection}},
	url = {https://etd.auburn.edu//handle/10415/888},
	abstract = {The process of finding and removing unexploded ordnance (UXO) from contaminated sites is an expensive and time consuming task.  In this thesis, an autonomous mobile robot-trailer system is developed for this purpose.  It is proposed that an autonomous robot can perform the task of UXO detected more efficiently and safely than current methods. 
 
In this thesis, a method of complete coverage path planning is developed that allows a path for surveying a field to be automatically generated.  Simple methods of obstacle avoidance are given that allow isolated, known obstacles in the field to be avoided.  A feedback control law is designed to guide a towed trailer to precisely follow a given path.  An experimental platform is designed consisting of a Segway RMP robot towing a trailer, guided by a GPS/INS positioning system.  Simulation and experimental results are provided to validate the control law. 
 
The effects of hitch angle measurement errors and noise in the GPS measurements on path tracking performance are analyzed.  The effects are examined for different sensor placements. Guidelines are provided for where the positioning sensors should be placed based on expected sensor errors and controller tunings.},
	language = {en\_US},
	urldate = {2024-06-20},
	author = {Hodo, David},
	month = aug,
	year = {2007},
}

The process of finding and removing unexploded ordnance (UXO) from contaminated sites is an expensive and time consuming task. In this thesis, an autonomous mobile robot-trailer system is developed for this purpose. It is proposed that an autonomous robot can perform the task of UXO detected more efficiently and safely than current methods. In this thesis, a method of complete coverage path planning is developed that allows a path for surveying a field to be automatically generated. Simple methods of obstacle avoidance are given that allow isolated, known obstacles in the field to be avoided. A feedback control law is designed to guide a towed trailer to precisely follow a given path. An experimental platform is designed consisting of a Segway RMP robot towing a trailer, guided by a GPS/INS positioning system. Simulation and experimental results are provided to validate the control law. The effects of hitch angle measurement errors and noise in the GPS measurements on path tracking performance are analyzed. The effects are examined for different sensor placements. Guidelines are provided for where the positioning sensors should be placed based on expected sensor errors and controller tunings.

@unpublished{wall_study_2007,
	type = {Thesis},
	title = {A {Study} of the {Effects} of {Stochastic} {Inertial} {Sensor} {Errors} in {Dead}-{Reckoning} {Navigation}},
	url = {https://etd.auburn.edu//handle/10415/945},
	abstract = {The research presented in this thesis seeks to quantify the error growth of navigation
frame attitude, velocity, and position as solely derived from acceleration and rotation-
rate measurements from a strapdown Inertial Measurement Unit (IMU). The wide-spread
availability of the Global Positioning System (GPS) and increased technological advances
in Inertial Navigation Systems (INS) technology has made possible the use of increasingly
affordable and compact GPS/INS navigation systems. While the fusion of GPS and
inertial sensing technology offers exceptional performance under nominal conditions, the
accuracy of the provided solution degrades rapidly when traveling under bridges, dense
foliage, or in urban canyons due to loss of communication with GPS satellites. The
degradation of the navigation solution in this inertial dead-reckoning mode is a direct
result of the numerical integration of stochastic errors exhibited by the inertial sensors
themselves. As the accuracy of the GPS/INS combined system depends heavily on the
standalone performance of the INS, firm quantification of the performance of inertial
dead-reckoning is imperative for system selection and design.

To provide quantification of the accuracy of inertial dead-reckoning, stochastic mod-
els are selected which approximate the noise and bias drift present on a wide variety of
both accelerometers and rate-gyroscopes. The stochastic identification techniques of Al-
lan variance and experimental autocorrelation are presented to illustrate the extraction
of process parameters from experimental data using the assumed model forms. The
selected models are then used to develop analytical expressions for the variance of subse-
quent integrations of the stochastic error processes. The resulting analytical expressions
are validated using Monte Carlo simulations. The analytical analysis is extended to a
simple navigation scenario in which a vehicle is constrained to travel on a planar surface
with no lateral velocity. Monte Carlo simulation techniques are employed to exemplify
and compare the expected results of inertial navigation in higher dynamic scenarios.},
	language = {en\_US},
	urldate = {2024-06-25},
	author = {Wall, John},
	month = aug,
	year = {2007},
	note = {Accepted: 2008-09-09T21:25:39Z},
}

The research presented in this thesis seeks to quantify the error growth of navigation frame attitude, velocity, and position as solely derived from acceleration and rotation- rate measurements from a strapdown Inertial Measurement Unit (IMU). The wide-spread availability of the Global Positioning System (GPS) and increased technological advances in Inertial Navigation Systems (INS) technology has made possible the use of increasingly affordable and compact GPS/INS navigation systems. While the fusion of GPS and inertial sensing technology offers exceptional performance under nominal conditions, the accuracy of the provided solution degrades rapidly when traveling under bridges, dense foliage, or in urban canyons due to loss of communication with GPS satellites. The degradation of the navigation solution in this inertial dead-reckoning mode is a direct result of the numerical integration of stochastic errors exhibited by the inertial sensors themselves. As the accuracy of the GPS/INS combined system depends heavily on the standalone performance of the INS, firm quantification of the performance of inertial dead-reckoning is imperative for system selection and design. To provide quantification of the accuracy of inertial dead-reckoning, stochastic mod- els are selected which approximate the noise and bias drift present on a wide variety of both accelerometers and rate-gyroscopes. The stochastic identification techniques of Al- lan variance and experimental autocorrelation are presented to illustrate the extraction of process parameters from experimental data using the assumed model forms. The selected models are then used to develop analytical expressions for the variance of subse- quent integrations of the stochastic error processes. The resulting analytical expressions are validated using Monte Carlo simulations. The analytical analysis is extended to a simple navigation scenario in which a vehicle is constrained to travel on a planar surface with no lateral velocity. Monte Carlo simulation techniques are employed to exemplify and compare the expected results of inertial navigation in higher dynamic scenarios.

@incollection{daily_sciautonics-auburn_2007,
	address = {Berlin, Heidelberg},
	title = {{SciAutonics}-{Auburn} {Engineering}’s {Low} {Cost} {High} {Speed} {ATV} for the 2005 {DARPA} {Grand} {Challenge}},
	isbn = {9783540734291},
	url = {https://doi.org/10.1007/978-3-540-73429-1_9},
	abstract = {This paper presents a summary of SciAutonics-Auburn Engineering’s efforts in the 2005 DARPA Grand Challenge. The areas discussed in detail include the team makeup and strategy, vehicle choice, software architecture, vehicle control, navigation, path planning, and obstacle detection. In particular, the advantages and complications involved in fielding a low budget all-terrain vehicle are presented. Emphasis is placed on detailing the methods used for high-speed control, customized navigation, and a novel stereo vision system. The platform chosen required a highly accurate model and a well-tuned navigation system in order to meet the demands of the Grand Challenge. Overall, the vehicle completed three out of four runs at the National Qualification Event and traveled 16 miles in the Grand Challenge before a hardware failure disabled operation. The performance in the events is described, along with a success and failure analysis.},
	language = {en},
	urldate = {2024-06-20},
	booktitle = {The 2005 {DARPA} {Grand} {Challenge}: {The} {Great} {Robot} {Race}},
	publisher = {Springer},
	author = {Daily, Robert and Travis, William and Bevly, David M. and Knoedler, Kevin and Behringer, Reinhold and Hemetsberger, Hannes and Kogler, Jürgen and Kubinger, Wilfried and Alefs, Bram},
	editor = {Buehler, Martin and Iagnemma, Karl and Singh, Sanjiv},
	year = {2007},
	doi = {10.1007/978-3-540-73429-1_9},
	pages = {281--309},
}

This paper presents a summary of SciAutonics-Auburn Engineering’s efforts in the 2005 DARPA Grand Challenge. The areas discussed in detail include the team makeup and strategy, vehicle choice, software architecture, vehicle control, navigation, path planning, and obstacle detection. In particular, the advantages and complications involved in fielding a low budget all-terrain vehicle are presented. Emphasis is placed on detailing the methods used for high-speed control, customized navigation, and a novel stereo vision system. The platform chosen required a highly accurate model and a well-tuned navigation system in order to meet the demands of the Grand Challenge. Overall, the vehicle completed three out of four runs at the National Qualification Event and traveled 16 miles in the Grand Challenge before a hardware failure disabled operation. The performance in the events is described, along with a success and failure analysis.

@inproceedings{lashley_analysis_2007,
	title = {Analysis of {Discriminator} {Based} {Vector} {Tracking} {Algorithms}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=7107},
	abstract = {In this paper, a variant of the vector delay lock loop (VDLL) tracking algorithm for tracking the L1 civilian GPS signal is introduced. The algorithm functions on the principle originally described in [1]. The VDLL architecture uses a single Extended Kalman Filter to predict the satellite PRN code phase and track the user’s position, velocity, and clock states. Additionally, a series of separate Kalman filters is used by each channel to track the satellite carrier signal. The advantages of the vector/Kalman filter based architecture over traditional methods are explained. The ability of the vector tracking algorithms to rapidly reacquire blocked signals is analyzed using data produced by a Spirent GPS simulator. The vector tracking algorithms performance is also compared to traditional methods using tracking loops. The VDLL is shown to outperform the traditional methods.},
	language = {en},
	urldate = {2024-06-20},
	author = {Lashley, Matthew and Bevly, David M.},
	month = jan,
	year = {2007},
	pages = {570--576},
}

In this paper, a variant of the vector delay lock loop (VDLL) tracking algorithm for tracking the L1 civilian GPS signal is introduced. The algorithm functions on the principle originally described in [1]. The VDLL architecture uses a single Extended Kalman Filter to predict the satellite PRN code phase and track the user’s position, velocity, and clock states. Additionally, a series of separate Kalman filters is used by each channel to track the satellite carrier signal. The advantages of the vector/Kalman filter based architecture over traditional methods are explained. The ability of the vector tracking algorithms to rapidly reacquire blocked signals is analyzed using data produced by a Spirent GPS simulator. The vector tracking algorithms performance is also compared to traditional methods using tracking loops. The VDLL is shown to outperform the traditional methods.

@article{pearson_modeling_2007,
	title = {Modeling and validation of hitch loading effects on tractor yaw dynamics},
	volume = {44},
	copyright = {https://www.elsevier.com/tdm/userlicense/1.0/},
	issn = {00224898},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0022489808000165},
	doi = {10.1016/j.jterra.2008.03.001},
	language = {en},
	number = {6},
	urldate = {2024-06-20},
	journal = {Journal of Terramechanics},
	author = {Pearson, Paul and Bevly, David M.},
	month = dec,
	year = {2007},
	pages = {439--450},
}

@article{lambert_weight_2007,
	title = {{WEIGHT} {SPLIT}'{S} {EFFECT} {ON} {VEHICLE} {ROLLOVER} {PROPENSITY} {AND} {ESC} {EFFECTIVENESS}},
	volume = {40},
	issn = {14746670},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S1474667015319777},
	doi = {10.3182/20070820-3-US-2918.00079},
	language = {en},
	number = {10},
	urldate = {2024-06-20},
	journal = {IFAC Proceedings Volumes},
	author = {Lambert, Kenneth and Bevly, David M.},
	year = {2007},
	pages = {587--592},
}

@inproceedings{edwards_method_2007,
	address = {Seattle, Washington, USA},
	title = {A {Method} to {Estimate} {Critical} {Tire} {Properties} {Using} {Non}-{Linear} {Tire} {Models}},
	isbn = {978-0-7918-4303-1},
	url = {https://asmedigitalcollection.asme.org/IMECE/proceedings/IMECE2007/43033/1137/329094},
	doi = {10.1115/IMECE2007-42064},
	abstract = {This paper describes a method to estimate lateral and longitudinal cornering stiffness, as well as the maximum tire force. Knowledge of these parameters can be critical for certain vehicle control systems that need to understand the tire’s limits, especially during turning maneuvers and acceleration. In this study, an extended Kalman filter is used along with the Dugoff or Fiala tire model to estimate these parameters. The pros and cons are discussed for estimation with both the Dugoff and Fiala tire models. An inertial measurement unit (IMU), a dual GPS antenna, and wheel speed sensors implemented on a test bed are used to evaluate the performance of the algorithms. A transformation matrix derived from a bicycle model is used to convert acceleration measurements into force measurements. The force measurements are then fed into the extended Kalman filter to estimate the parameters. Although this algorithm is post-processed, it can easily be used in real-time estimation. The experiment is performed on an asphalt surface to test its performance. The effects of vehicle roll can be significant for vehicles that exhibit large roll angles, but it is assumed to be negligible in this study.},
	urldate = {2024-06-20},
	booktitle = {Volume 9: {Mechanical} {Systems} and {Control}, {Parts} {A}, {B}, and {C}},
	publisher = {ASMEDC},
	author = {Edwards, Dustin L. and Bevly, David M.},
	month = jan,
	year = {2007},
	pages = {1137--1146},
}

This paper describes a method to estimate lateral and longitudinal cornering stiffness, as well as the maximum tire force. Knowledge of these parameters can be critical for certain vehicle control systems that need to understand the tire’s limits, especially during turning maneuvers and acceleration. In this study, an extended Kalman filter is used along with the Dugoff or Fiala tire model to estimate these parameters. The pros and cons are discussed for estimation with both the Dugoff and Fiala tire models. An inertial measurement unit (IMU), a dual GPS antenna, and wheel speed sensors implemented on a test bed are used to evaluate the performance of the algorithms. A transformation matrix derived from a bicycle model is used to convert acceleration measurements into force measurements. The force measurements are then fed into the extended Kalman filter to estimate the parameters. Although this algorithm is post-processed, it can easily be used in real-time estimation. The experiment is performed on an asphalt surface to test its performance. The effects of vehicle roll can be significant for vehicles that exhibit large roll angles, but it is assumed to be negligible in this study.

@inproceedings{huang_3d_2007,
	address = {Seattle, Washington, USA},
	title = {{3D} {Road} {Geometry} {Based} {Optimal} {Truck} {Fuel} {Economy}},
	isbn = {978-0-7918-4310-9},
	url = {https://asmedigitalcollection.asme.org/IMECE/proceedings/IMECE2007/43106/63/326606},
	doi = {10.1115/IMECE2007-41695},
	abstract = {This paper investigates the benefit of using a 3D road geometry based optimal powertrain control strategy in reducing the fuel consumption of heavy trucks. The optimal control, which applies a sequential quadratic programming (SQP) method, is designed to predict the optimal truck velocity trajectory, based on the road geometry with the consideration of fuel consumption and travel time. The fuel consumption baseline is developed based on an engineering drive cycle. Computer simulations of a Class 8 truck are conducted with Intermap real 3D road geometry. Simulation results show that the optimal control strategy is able to reduce the fuel consumption with equal or even shorter travel time, when compared to the defined baseline.},
	urldate = {2024-06-20},
	booktitle = {Volume 16: {Transportation} {Systems}},
	publisher = {ASMEDC},
	author = {Huang, Wei and Bevly, David M. and Li, Xiaopeng and Schnick, Steve},
	month = jan,
	year = {2007},
	pages = {63--70},
}

This paper investigates the benefit of using a 3D road geometry based optimal powertrain control strategy in reducing the fuel consumption of heavy trucks. The optimal control, which applies a sequential quadratic programming (SQP) method, is designed to predict the optimal truck velocity trajectory, based on the road geometry with the consideration of fuel consumption and travel time. The fuel consumption baseline is developed based on an engineering drive cycle. Computer simulations of a Class 8 truck are conducted with Intermap real 3D road geometry. Simulation results show that the optimal control strategy is able to reduce the fuel consumption with equal or even shorter travel time, when compared to the defined baseline.

@inproceedings{miller_position_2007,
	title = {Position and {Orientation} {Determination} for a {Guided} {K}-9},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=7386},
	abstract = {A GPS/INS sensor suite was attached by a vest to a canine (K-9) in order to attain characteristic position and orientation data during typical K-9 behavioral motions such as walking, trotting, sitting, and turning. For better accuracy, the sensors were combined using an Extended Kalman Filter (EKF), which has been done for other GPS/INS integrated systems [1-3] and then examined to see if the position and orientation EKF outputs correctly portrayed the K-9 motions. Special tuning of the EKF was required due to the unique motion characteristics inherent in canines. However, the EKF was found to be effective in achieving relatively accurate position and orientation tracking results for the canine. Results show that the low-cost GPS/INS system can provide information about the canine’s motion, including the canine’s current position and heading.},
	language = {en},
	urldate = {2024-06-20},
	author = {Miller, Jeff and Bevly, David M.},
	month = sep,
	year = {2007},
	pages = {1768--1776},
}

A GPS/INS sensor suite was attached by a vest to a canine (K-9) in order to attain characteristic position and orientation data during typical K-9 behavioral motions such as walking, trotting, sitting, and turning. For better accuracy, the sensors were combined using an Extended Kalman Filter (EKF), which has been done for other GPS/INS integrated systems [1-3] and then examined to see if the position and orientation EKF outputs correctly portrayed the K-9 motions. Special tuning of the EKF was required due to the unique motion characteristics inherent in canines. However, the EKF was found to be effective in achieving relatively accurate position and orientation tracking results for the canine. Results show that the low-cost GPS/INS system can provide information about the canine’s motion, including the canine’s current position and heading.

@inproceedings{hodo_effects_2007,
	title = {Effects of {Sensor} {Placement} and {Errors} on {Path} {Following} {Control} of a {Mobile} {Robot}-{Trailer} {System}},
	url = {https://ieeexplore.ieee.org/abstract/document/4282739},
	doi = {10.1109/ACC.2007.4282739},
	abstract = {In this paper, effects of sensor location and measurement errors on path tracking control of a mobile robot pulling a trailer are reported. A model for a two-wheeled robot towing a trailer is presented, followed by a state feedback controller designed to position the trailer along a path consisting of lines and circular arcs. An incremental encoder is used to measure the hitch angle between the robot and trailer. A combined GPS/IMU system is used to measure position and orientation of either the robot or the trailer (but not both). The choice of mounting location for the GPS/IMU system, and consequent effects on trailer path tracking performance are explored. The sensitivity of the system to hitch angle errors is also examined for both cases. It is shown that the system is less sensitive to errors in the hitch angle measurement when the GPS/IMU system is located on the trailer.},
	urldate = {2024-06-20},
	booktitle = {2007 {American} {Control} {Conference}},
	author = {Hodo, David W. and Hung, John Y. and Bevly, David M. and Millhouse, Scott},
	month = jul,
	year = {2007},
	note = {ISSN: 2378-5861},
	keywords = {Control systems, Error correction, Global Positioning System, Goniometers, Measurement errors, Mobile robots, Position measurement, Robot sensing systems, Sensor systems, State feedback},
	pages = {2165--2170},
}

In this paper, effects of sensor location and measurement errors on path tracking control of a mobile robot pulling a trailer are reported. A model for a two-wheeled robot towing a trailer is presented, followed by a state feedback controller designed to position the trailer along a path consisting of lines and circular arcs. An incremental encoder is used to measure the hitch angle between the robot and trailer. A combined GPS/IMU system is used to measure position and orientation of either the robot or the trailer (but not both). The choice of mounting location for the GPS/IMU system, and consequent effects on trailer path tracking performance are explored. The sensitivity of the system to hitch angle errors is also examined for both cases. It is shown that the system is less sensitive to errors in the hitch angle measurement when the GPS/IMU system is located on the trailer.

@inproceedings{lashley_comparison_2007,
	title = {Comparison of {Traditional} {Tracking} {Loops} and {Vector} {Based} {Tracking} {Loops} for {Weak} {GPS} {Signals}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=7579},
	abstract = {In this paper, a variant of the Vector Delay/Frequency Lock Loop (VDFLL) algorithm is introduced for the GPS L1 civilian signal. The VDFLL algorithm uses a single Extended Kalman Filter (EKF) to simultaneously track the GPS signals and determine the user’s navigation states. The states of the EKF are the user’s position, velocity, acceleration, clock bias, and clock drift. The carrier frequency and Pseudo-Random Noise (PRN) code phase for each satellite are predicted based on the states of the EKF. Unlike traditional approaches, the VDFLL algorithm does not use Delay Lock Loops (DLL’s) or Costas Loops to track the GPS signals. The VDFLL algorithm has the ability to track weak GPS signals and rapidly reacquire blocked signals. The performance of the VDFLL is compared to that of a high end commercial receiver in an environment with dense foliage and rapidly fluctuating signal levels. The experimental results show that the VDFLL outperforms the commercial receiver and provides continuous coverage in GPS challenged environment.},
	language = {en},
	urldate = {2024-06-20},
	author = {Lashley, Matthew and Bevly, David M.},
	month = sep,
	year = {2007},
	pages = {789--795},
}

In this paper, a variant of the Vector Delay/Frequency Lock Loop (VDFLL) algorithm is introduced for the GPS L1 civilian signal. The VDFLL algorithm uses a single Extended Kalman Filter (EKF) to simultaneously track the GPS signals and determine the user’s navigation states. The states of the EKF are the user’s position, velocity, acceleration, clock bias, and clock drift. The carrier frequency and Pseudo-Random Noise (PRN) code phase for each satellite are predicted based on the states of the EKF. Unlike traditional approaches, the VDFLL algorithm does not use Delay Lock Loops (DLL’s) or Costas Loops to track the GPS signals. The VDFLL algorithm has the ability to track weak GPS signals and rapidly reacquire blocked signals. The performance of the VDFLL is compared to that of a high end commercial receiver in an environment with dense foliage and rapidly fluctuating signal levels. The experimental results show that the VDFLL outperforms the commercial receiver and provides continuous coverage in GPS challenged environment.

@unpublished{travis_methods_2006,
	type = {Thesis},
	title = {Methods for {Minimizing} {Navigation} {Errors} {Induced} by {Ground} {Vehicle} {Dynamics}},
	url = {https://etd.auburn.edu//handle/10415/400},
	abstract = {A navigation system was designed using an extended Kalman filter for an autonomous ground vehicle competing in the 2005 DARPA Grand Challenge.  An overview of this system is provided, and errors in the navigation solution are explained.  These errors are attributed to vehicle dynamics unaccounted for in the navigation model.

Investigation of these errors begins with the development of a nonlinear simulation to provide vehicle state information in a controlled environment.  These vehicle states are used in various navigation models to show difference in navigation accuracy when lateral vehicle dynamics are taken into account.  Accuracy with and without GPS measurements is examined.  The study then utilizes experimental data to provide similar results.  Also, sources of error stemming from typical velocity sensors are explained.

Finally, a method is proposed to utilize a laser scanner to provide measurements for use in the navigation models incorporating lateral vehicle motion.  This method could also be used to provide a vehicle controller lateral error from a defined corridor.  The method is explained, and experimental results from a simple test bed are shown.},
	language = {en\_US},
	urldate = {2024-06-25},
	author = {Travis, William},
	month = may,
	year = {2006},
	note = {Accepted: 2008-09-09T21:17:27Z},
}

A navigation system was designed using an extended Kalman filter for an autonomous ground vehicle competing in the 2005 DARPA Grand Challenge. An overview of this system is provided, and errors in the navigation solution are explained. These errors are attributed to vehicle dynamics unaccounted for in the navigation model. Investigation of these errors begins with the development of a nonlinear simulation to provide vehicle state information in a controlled environment. These vehicle states are used in various navigation models to show difference in navigation accuracy when lateral vehicle dynamics are taken into account. Accuracy with and without GPS measurements is examined. The study then utilizes experimental data to provide similar results. Also, sources of error stemming from typical velocity sensors are explained. Finally, a method is proposed to utilize a laser scanner to provide measurements for use in the navigation models incorporating lateral vehicle motion. This method could also be used to provide a vehicle controller lateral error from a defined corridor. The method is explained, and experimental results from a simple test bed are shown.

@unpublished{newlin_design_2006,
	type = {Thesis},
	title = {Design and {Development} of a {GPS} {Intermediate} {Frequency} and {IMU} {Data} {Acquisition} {System} for {Advanced} {Integrated} {Architectures}},
	url = {https://etd.auburn.edu//handle/10415/614},
	abstract = {Advanced levels of GPS and INS integration, including Deeply Integrated and Ultra-
Tightly Coupled, have been reported to provide significant gains in anti-jamming capa-
bility and reduced susceptibility to loss of GPS signal lock. This thesis provides the
design and development of a GPS intermediate frequency and IMU data acquisition
system that can be used for the implementation of these advanced GPS and INS inte-
grated algorithms. Details of the design of the system are covered, including GPS chip
set selection, signal conditioning, and data collection. The system is capable of syn-
chronizing IMU measurement collection to the collection of digitized GPS intermediate
frequency in real-time using a derivative of the GPS IF sampling clock to sample the
IMU measurements. This synchronization is necessary for proper integrated algorithm
implementation. The system was installed on a moving platform and the results of the
experiment are shown using a GPS software receiver for the validation of the digitized
GPS IF and the plotting of the IMU measurements.},
	language = {en\_US},
	urldate = {2024-06-25},
	author = {Newlin, Michael},
	month = dec,
	year = {2006},
	note = {Accepted: 2008-09-09T21:20:30Z},
}

Advanced levels of GPS and INS integration, including Deeply Integrated and Ultra- Tightly Coupled, have been reported to provide significant gains in anti-jamming capa- bility and reduced susceptibility to loss of GPS signal lock. This thesis provides the design and development of a GPS intermediate frequency and IMU data acquisition system that can be used for the implementation of these advanced GPS and INS inte- grated algorithms. Details of the design of the system are covered, including GPS chip set selection, signal conditioning, and data collection. The system is capable of syn- chronizing IMU measurement collection to the collection of digitized GPS intermediate frequency in real-time using a derivative of the GPS IF sampling clock to sample the IMU measurements. This synchronization is necessary for proper integrated algorithm implementation. The system was installed on a moving platform and the results of the experiment are shown using a GPS software receiver for the validation of the digitized GPS IF and the plotting of the IMU measurements.

@unpublished{lashley_kalman_2006,
	type = {Thesis},
	title = {Kalman {Filter} {Based} {Tracking} {Algorithms} {For} {Software} {GPS} {Receivers}},
	url = {https://etd.auburn.edu//handle/10415/611},
	abstract = {In this thesis several new Kalman filter based tracking algorithms for GPS software
receivers are presented. Traditional receivers use Costas loops and Delay Lock Loops
(DLL) to track the carrier and Pseudo-Random Noise (PRN) signals broadcast by the
GPS satellites, respectively. The tasks of tracking the the carrier and PRN signals are
done separately. The Kalman filter based algorithms introduced in this thesis provide
an alternative to the Costas loop and DLL. The task of tracking the PRN sequences is
handled by a single Extended Kalman Filter (EKF). The EKF is used to estimate the
user’s position in the Earth-Centered Earth-Fixed (ECEF) coordinate frame. Using the
EKF’s estimates, the code phases of the PRN sequences being received from the different
satellites are predicted. Estimates of the code phase error between the predicted and
received codes are generated using discriminator functions. The estimates of the code
phase errors are used to update the EKF’s estimates of the user’s navigation states.
To provide proof of concept, data was collected using a Spirent GPS simulator. The
recorded data was used to show that the new Kalman filter based algorithms outperform
traditional tracking methods.},
	language = {en\_US},
	urldate = {2024-06-25},
	author = {Lashley, Matthew},
	month = dec,
	year = {2006},
	note = {Accepted: 2008-09-09T21:20:27Z},
}

In this thesis several new Kalman filter based tracking algorithms for GPS software receivers are presented. Traditional receivers use Costas loops and Delay Lock Loops (DLL) to track the carrier and Pseudo-Random Noise (PRN) signals broadcast by the GPS satellites, respectively. The tasks of tracking the the carrier and PRN signals are done separately. The Kalman filter based algorithms introduced in this thesis provide an alternative to the Costas loop and DLL. The task of tracking the PRN sequences is handled by a single Extended Kalman Filter (EKF). The EKF is used to estimate the user’s position in the Earth-Centered Earth-Fixed (ECEF) coordinate frame. Using the EKF’s estimates, the code phases of the PRN sequences being received from the different satellites are predicted. Estimates of the code phase error between the predicted and received codes are generated using discriminator functions. The estimates of the code phase errors are used to update the EKF’s estimates of the user’s navigation states. To provide proof of concept, data was collected using a Spirent GPS simulator. The recorded data was used to show that the new Kalman filter based algorithms outperform traditional tracking methods.

@unpublished{heffernan_simulation_2006,
	type = {Thesis},
	title = {Simulation, {Estimation}, and {Experimentation} of {Vehicle} {Longitudinal} {Dynamics} {That} {Effect} {Fuel} {Economy}},
	url = {https://etd.auburn.edu//handle/10415/239},
	abstract = {In this thesis, longitudinal vehicle dynamics are researched with an emphasis on heavy trucks and fuel economy. Commercial vehicles display large variations in their parameters, and due to many current trends in transportation systems, estimating these parameters has been the subject of much research. Additionally, fuel economy enhancement has become a major issue due to man-kind’s reliance on oil. In this research a longitudinal truck model is developed and the longitudinal dynamics are simulated in various conditions. Algorithms are developed to estimate vehicle parameters and are used in simulation to perform an analysis of their accuracy. Simulated results show the difficulty of estimating individual vehicle parameters in the presence of sensor noise and low levels of vehicle excitation, such as with the heavy trucks at the Auburn University National Center for Asphalt Technology facility. Finally, a class 8 commercial vehicle is instrumented as a test-bed. Estimation results from the test bed support the simulation, while simple parameters are shown to be identified with reasonable accuracy. Road load data for fuel economy evaluation was also collected on the trucks and variations over the asphalt sections are shown.},
	language = {en\_US},
	urldate = {2024-06-25},
	author = {Heffernan, Matthew},
	month = aug,
	year = {2006},
	note = {Accepted: 2008-09-09T21:15:31Z},
}

In this thesis, longitudinal vehicle dynamics are researched with an emphasis on heavy trucks and fuel economy. Commercial vehicles display large variations in their parameters, and due to many current trends in transportation systems, estimating these parameters has been the subject of much research. Additionally, fuel economy enhancement has become a major issue due to man-kind’s reliance on oil. In this research a longitudinal truck model is developed and the longitudinal dynamics are simulated in various conditions. Algorithms are developed to estimate vehicle parameters and are used in simulation to perform an analysis of their accuracy. Simulated results show the difficulty of estimating individual vehicle parameters in the presence of sensor noise and low levels of vehicle excitation, such as with the heavy trucks at the Auburn University National Center for Asphalt Technology facility. Finally, a class 8 commercial vehicle is instrumented as a test-bed. Estimation results from the test bed support the simulation, while simple parameters are shown to be identified with reasonable accuracy. Road load data for fuel economy evaluation was also collected on the trucks and variations over the asphalt sections are shown.

@unpublished{clanton_gps_2006,
	type = {Thesis},
	title = {{GPS} and {Inertial} {Sensor} {Enhancements} for {Vision}-based {Highway} {Lane} {Tracking}},
	url = {https://etd.auburn.edu//handle/10415/324},
	abstract = {For the past decade much research in the Intelligent Transportation Systems (ITS)
community has been devoted to the topic of lane departure warning (LDW). A significant
portion of highway fatalities each year are attributed to vehicle lane departure. Many
automobile manufacturers are developing advanced driver assistance systems, many of
which include subsystems that help prevent un-intended lane departure. A consistent
approach among these systems is to alert the driver when an un-intended lane departure
is predicted. To predict a possible lane departure, a vision system mounted on the vehi-
cle detects the lane markings on the road and determines the vehicle’s orientation and
position with respect to the detected lane lines. These vision-based systems suffer from
performance limitations that are brought forth by environmental constraints. Therefore,
it is desirable to add support from additional sensors to compensate when the vision
system loses its ability to perform lane departure warning.

The first goal of this research is to present current methods of vision-based LDW systems and to explore methods of sensor enhancement to assist the vision system. Sec-
ond, several image processing and computer vision algorithms will be implemented as
demonstration of how they could be used in a vision-based LDW system. Finally, the
main goal of this research is to develop a method using additional sensors such as GPS
and inertial sensors to enhance vision-based lane detection.

The combination of GPS and the vision system together with a high accuracy lane-
level map will allow a more robust highway lane tracking system. Kalman filtering is
employed to incorporate inertial sensor inputs and measurements from the GPS receiver
and vision system to estimate the vehicle states relative to highway lane tracking. Vehicle
lateral offset, lateral velocity and heading angle are estimated to provide lane tracking
when the vision-based lateral offset measurement fails.},
	language = {en\_US},
	urldate = {2024-06-25},
	author = {Clanton, Joshua},
	month = aug,
	year = {2006},
	note = {Accepted: 2008-09-09T21:16:31Z},
}

For the past decade much research in the Intelligent Transportation Systems (ITS) community has been devoted to the topic of lane departure warning (LDW). A significant portion of highway fatalities each year are attributed to vehicle lane departure. Many automobile manufacturers are developing advanced driver assistance systems, many of which include subsystems that help prevent un-intended lane departure. A consistent approach among these systems is to alert the driver when an un-intended lane departure is predicted. To predict a possible lane departure, a vision system mounted on the vehi- cle detects the lane markings on the road and determines the vehicle’s orientation and position with respect to the detected lane lines. These vision-based systems suffer from performance limitations that are brought forth by environmental constraints. Therefore, it is desirable to add support from additional sensors to compensate when the vision system loses its ability to perform lane departure warning. The first goal of this research is to present current methods of vision-based LDW systems and to explore methods of sensor enhancement to assist the vision system. Sec- ond, several image processing and computer vision algorithms will be implemented as demonstration of how they could be used in a vision-based LDW system. Finally, the main goal of this research is to develop a method using additional sensors such as GPS and inertial sensors to enhance vision-based lane detection. The combination of GPS and the vision system together with a high accuracy lane- level map will allow a more robust highway lane tracking system. Kalman filtering is employed to incorporate inertial sensor inputs and measurements from the GPS receiver and vision system to estimate the vehicle states relative to highway lane tracking. Vehicle lateral offset, lateral velocity and heading angle are estimated to provide lane tracking when the vision-based lateral offset measurement fails.

@unpublished{anderson_design_2006,
	type = {Thesis},
	title = {Design, {Testing}, and {Simulation} of a {Low}-{Cost}, {Light}-{Weight}, {Low}-g {IMU} for the {Navigation} of an {Indoor} {Blimp}},
	url = {https://etd.auburn.edu//handle/10415/443},
	abstract = {In this thesis we develop an IMU for the purpose of navigating an autonomous indoor blimp. Due to the unique system properties of an indoor blimp, the developed IMU is light-weight and is capable of measuring slow rotational rates and accelerations. An emphasis is placed on maintaining low cost by using commercially available off-the-shelf components.

We present an overview of current IMU technology and evaluate that technology's suitability for use with an indoor blimp. Through this evaluation we conclude that commercially available IMUs are not viable so an IMU must be designed. We present design constraints that must be met and evaluate commercially available sensors that can meet these constraints. After selecting the most appropriate hardware, we integrate the sensors to form an IMU.

The constructed IMU is tested, modeled, and simulated. We test the IMU by applying known constant inputs and evaluating the sensors' outputs. Models of the sensors are developed from the test data. The models are then evaluated based on autocorrelation methods. Based on experimental observations, we also develop a mathematical model of an indoor blimp in closed loop with guidance and control laws. We perform several simulations to evaluate the IMU's ability to accurately measure the blimp's states.},
	language = {en\_US},
	urldate = {2024-06-25},
	author = {Anderson, Abby},
	month = may,
	year = {2006},
	note = {Accepted: 2008-09-09T21:17:59Z},
}

In this thesis we develop an IMU for the purpose of navigating an autonomous indoor blimp. Due to the unique system properties of an indoor blimp, the developed IMU is light-weight and is capable of measuring slow rotational rates and accelerations. An emphasis is placed on maintaining low cost by using commercially available off-the-shelf components. We present an overview of current IMU technology and evaluate that technology's suitability for use with an indoor blimp. Through this evaluation we conclude that commercially available IMUs are not viable so an IMU must be designed. We present design constraints that must be met and evaluate commercially available sensors that can meet these constraints. After selecting the most appropriate hardware, we integrate the sensors to form an IMU. The constructed IMU is tested, modeled, and simulated. We test the IMU by applying known constant inputs and evaluating the sensors' outputs. Models of the sensors are developed from the test data. The models are then evaluated based on autocorrelation methods. Based on experimental observations, we also develop a mathematical model of an indoor blimp in closed loop with guidance and control laws. We perform several simulations to evaluate the IMU's ability to accurately measure the blimp's states.

@inproceedings{bevly_estimation_2006,
	address = {Warrendale, PA},
	title = {Estimation of {Critical} {Tire} {Parameters} {Using} {GPS} {Based} {Sideslip} {Measurements}},
	url = {https://www.sae.org/publications/technical-papers/content/2006-01-1965/},
	abstract = {This paper investigates the use of GPS to estimate vehicle sideslip and tire information.  Both a one-antenna GPS antenna/receiver and dual GPS antenna method are studied.  Analysis of the accuracy that can be achieved using the two different GPS solutions is provided.  The algorithms are then valid},
	language = {English},
	urldate = {2024-06-20},
	publisher = {SAE Technical Paper},
	author = {Bevly, David M. and Daily, Robert and Travis, William},
	month = feb,
	year = {2006},
	doi = {10.4271/2006-01-1965},
}

This paper investigates the use of GPS to estimate vehicle sideslip and tire information. Both a one-antenna GPS antenna/receiver and dual GPS antenna method are studied. Analysis of the accuracy that can be achieved using the two different GPS solutions is provided. The algorithms are then valid

@inproceedings{wall_characterization_2006,
	title = {Characterization of {Inertial} {Sensor} {Measurements} for {Navigation} {Performance} {Analysis}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=6774},
	abstract = {This paper develops analytical and empirical bounds on the inertial sensor error growth due to the numerical integration of rotation rate and acceleration outputs of various grade inertial measurement units (IMU). The developed error bounds provide an explicit measure of the performance of the IMU when it is the sole means of navigation. Accurate analysis of inertial sensor error growth is essential to ensuring the effectiveness of the optimal synergy of GPS and inertial measurements, as success is often limited by the availability of GPS signals in harsh environments. Studies of inertial sensors and their associated error modes have been developed resulting in the wide use of these models for use in GPS/INS algorithms. This paper presents an analysis of the IMU models to investigate the behaviors of inertial navigation error growth due to the subsequent integrations of the raw measurements in dead reckoning. The main purpose of this study is to provide quantitative specification on the degradation of navigation solutions when dead reckoning with IMUs. The parameters characterizing the sensor models for which the error analysis is performed are identified using autocorrelation and Allan variance techniques and the resulting analytical based formulations are validated using Monte Carlo simulation methods.},
	language = {en},
	urldate = {2024-06-20},
	author = {Wall, J. H. and Bevly, D. M.},
	month = sep,
	year = {2006},
	pages = {2678--2685},
}

This paper develops analytical and empirical bounds on the inertial sensor error growth due to the numerical integration of rotation rate and acceleration outputs of various grade inertial measurement units (IMU). The developed error bounds provide an explicit measure of the performance of the IMU when it is the sole means of navigation. Accurate analysis of inertial sensor error growth is essential to ensuring the effectiveness of the optimal synergy of GPS and inertial measurements, as success is often limited by the availability of GPS signals in harsh environments. Studies of inertial sensors and their associated error modes have been developed resulting in the wide use of these models for use in GPS/INS algorithms. This paper presents an analysis of the IMU models to investigate the behaviors of inertial navigation error growth due to the subsequent integrations of the raw measurements in dead reckoning. The main purpose of this study is to provide quantitative specification on the degradation of navigation solutions when dead reckoning with IMUs. The parameters characterizing the sensor models for which the error analysis is performed are identified using autocorrelation and Allan variance techniques and the resulting analytical based formulations are validated using Monte Carlo simulation methods.

@inproceedings{clark_analysis_2006,
	title = {Analysis of {Improvement} to {Two}-{Wheel} {Robot} {Navigation} {Using} {Low}-{Cost} {GPS}/{INS} {Aids}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=6940},
	abstract = {This paper shows the use of sensor fusion (GPS/INS/odometry) to estimate and eliminate errors which are unobservable for a two-wheeled robot using odometry information alone, including the accuracy benefit that combinations of these sensors provide. The combinations examined are GPS/odometry and INS/odometry, both of which are low-cost options. It is shown that the effects of longitudinal wheel slip and tire radius error can be lumped together as an ‘effective radius’ and estimated effectively using GPS velocity and course measurements. This estimated radius can account for these error modes at the speed at which it was estimated but the estimation effectiveness degrades as speed changes. This paper shows the improvement to the navigation of a two-wheel robot platform using this estimation method.},
	language = {en},
	urldate = {2024-06-20},
	author = {Clark, B. J. and Bevly, D. M. and Farritor, S.},
	month = sep,
	year = {2006},
	pages = {1440--1448},
}

This paper shows the use of sensor fusion (GPS/INS/odometry) to estimate and eliminate errors which are unobservable for a two-wheeled robot using odometry information alone, including the accuracy benefit that combinations of these sensors provide. The combinations examined are GPS/odometry and INS/odometry, both of which are low-cost options. It is shown that the effects of longitudinal wheel slip and tire radius error can be lumped together as an ‘effective radius’ and estimated effectively using GPS velocity and course measurements. This estimated radius can account for these error modes at the speed at which it was estimated but the estimation effectiveness degrades as speed changes. This paper shows the improvement to the navigation of a two-wheel robot platform using this estimation method.

@inproceedings{clanton_highway_2006,
	title = {Highway {Lane} {Tracking} {Using} {GPS} in {Conjunction} {With} {Onboard} {IMU} and {Vision}-based {Lane} {Tracking} {Measurements}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=6777},
	abstract = {When a vehicle’s Lane Departure Warning (LDW) system fails to detect lane markers on the roadway ahead of the vehicle, it loses its ability to alert the driver of an unintended lane departure. Therefore, it has been a recent trend in LDW research to explore the use of use multiple sensors, such as GPS and inertial measurement units (IMU) to assist the LDW vision system in the event of a lane detection failure [5][7]. These multi-sensor systems typically use differential GPS or even real-time kinematic (RTK) GPS combined with high accuracy maps to locate the vehicle to within a particular lane on a roadway. Although these advanced positioning systems are highly accurate, they are currently not deployed in the consumer automobile market, so therefore, are currently not cost effective solutions. The goal of this research is to use regular GPS, combined with inertial sensors and a high accuracy map to assist a vision-based lane departure warning system. In-car GPS navigation systems are available in many automobiles, as well as automotive grade inertial sensors. The low accuracy of a typical GPS receiver found in an automotive navigation system is largely attributed to a position error. This error is too large to allow the GPS receiver to locate a vehicle in a particular lane on a roadway. This work will present a method to measure this error using a vision-based lane departure warning system together with a high-accuracy map. With the error known, the accuracy of the GPS receiver is increased to a high-enough level to localize the vehicle on a particular lane. Next, this work will present a method fusing GPS/INS/Vision and a high accuracy map for highway lane tracking. The goal of this method is to provide a backup lateral offset measurement that can be used for lane departure warning, when the LDW vision system loses track of the lane markings.},
	language = {en},
	urldate = {2024-06-20},
	author = {Clanton, J. M. and Bevly, D. M. and Hodel, A. S.},
	month = sep,
	year = {2006},
	pages = {1076--1084},
}

When a vehicle’s Lane Departure Warning (LDW) system fails to detect lane markers on the roadway ahead of the vehicle, it loses its ability to alert the driver of an unintended lane departure. Therefore, it has been a recent trend in LDW research to explore the use of use multiple sensors, such as GPS and inertial measurement units (IMU) to assist the LDW vision system in the event of a lane detection failure [5][7]. These multi-sensor systems typically use differential GPS or even real-time kinematic (RTK) GPS combined with high accuracy maps to locate the vehicle to within a particular lane on a roadway. Although these advanced positioning systems are highly accurate, they are currently not deployed in the consumer automobile market, so therefore, are currently not cost effective solutions. The goal of this research is to use regular GPS, combined with inertial sensors and a high accuracy map to assist a vision-based lane departure warning system. In-car GPS navigation systems are available in many automobiles, as well as automotive grade inertial sensors. The low accuracy of a typical GPS receiver found in an automotive navigation system is largely attributed to a position error. This error is too large to allow the GPS receiver to locate a vehicle in a particular lane on a roadway. This work will present a method to measure this error using a vision-based lane departure warning system together with a high-accuracy map. With the error known, the accuracy of the GPS receiver is increased to a high-enough level to localize the vehicle on a particular lane. Next, this work will present a method fusing GPS/INS/Vision and a high accuracy map for highway lane tracking. The goal of this method is to provide a backup lateral offset measurement that can be used for lane departure warning, when the LDW vision system loses track of the lane markings.

@unpublished{hamm_analysis_2005,
	type = {Thesis},
	title = {Analysis of {Simulated} {Performance} of {Integrated} {Vector} {Tracking} and {Navigation} {Loops} for {GPS}},
	url = {https://etd.auburn.edu//handle/10415/378},
	abstract = {An alternative GPS signal tracking method that uses an extended Kalman-Bucy filter in place of traditional independent, parallel tracking loops is presented in this thesis. Furthermore, this method is extended into a combined tracking and navigation filter coupled with inertial sensors. This approach significantly reduces filter design complexity  and allows for optimal navigation performance in a variety of conditions. Specifically, the proposed method is demonstrated under high dynamic platform motion while experiencing significant levels of jamming. A simulation in a single-axis configuration was used to compare the proposed method to an existing, aided fixed-gain method in order to ascertain the expected level of anti-jam performance as well as immunity to dynamic stress. Results from this simulation indicate a nominal, expected positioning performance improvement of 5 meters with improvements of up to 25 meters in some cases. Additionally, increased jamming immunity of 17 dB J/S was seen in the simulations. A simulation comparing IMU's of differing grades was also run to ascertain the proposed method's dependence upon inertial sensor quality.},
	language = {en\_US},
	urldate = {2024-06-25},
	author = {Hamm, Christopher},
	month = dec,
	year = {2005},
	note = {Accepted: 2008-09-09T21:17:11Z},
}

An alternative GPS signal tracking method that uses an extended Kalman-Bucy filter in place of traditional independent, parallel tracking loops is presented in this thesis. Furthermore, this method is extended into a combined tracking and navigation filter coupled with inertial sensors. This approach significantly reduces filter design complexity and allows for optimal navigation performance in a variety of conditions. Specifically, the proposed method is demonstrated under high dynamic platform motion while experiencing significant levels of jamming. A simulation in a single-axis configuration was used to compare the proposed method to an existing, aided fixed-gain method in order to ascertain the expected level of anti-jam performance as well as immunity to dynamic stress. Results from this simulation indicate a nominal, expected positioning performance improvement of 5 meters with improvements of up to 25 meters in some cases. Additionally, increased jamming immunity of 17 dB J/S was seen in the simulations. A simulation comparing IMU's of differing grades was also run to ascertain the proposed method's dependence upon inertial sensor quality.

@unpublished{gartley_-line_2005,
	type = {Thesis},
	title = {On-line {Estimation} of {Implement} {Dynamics} for {Adaptive} {Steering} {Control} of {Farm} {Tractors}},
	url = {https://etd.auburn.edu//handle/10415/354},
	abstract = {An adaptive control technique for the control of a farm tractor during low levels of excitation and at low velocities is presented.  Results of a set of system identification experiments are compared to previous tractor models.  A cascaded controller is then designed for the feedback of steer angle, yaw rate, and lateral position baed on the new tractor model.  An on-line analysis of the data is used to determine if enough excitation is available for adaptation.  A cascaded Kalman Filter is presented to estimate the slope of the DC gain of the steer angle to yaw rate transfer function, MDC, with respect to velocity.  An estimator also provides faster updates of position.  From the on-line estimate of MDC, the controller gains are scheduled based on a lookup table of predetermined values that were calculated from system identification tests.

The sensitivity of the controller to model simplifications, incorrect velocities, and MDC estimate errors are investigated.  The accuracy of the estimated MDC due to neglected dynamics and the rate of convergence is shown.  A simulation is used to show the errors that can be induced in the position estimator by the GPS delay.  The yaw rate estimator is designed for fixed point math using a square root covariance filter.  Experimental and simulation results are provided which show the validity of the MDC estimate.  Finally, experimental results which show that the accuracy changes little as a result of hitch loading and velocity are presented and discussed.},
	language = {en\_US},
	urldate = {2024-06-25},
	author = {Gartley, Evan},
	month = dec,
	year = {2005},
	note = {Accepted: 2008-09-09T21:16:53Z},
}

An adaptive control technique for the control of a farm tractor during low levels of excitation and at low velocities is presented. Results of a set of system identification experiments are compared to previous tractor models. A cascaded controller is then designed for the feedback of steer angle, yaw rate, and lateral position baed on the new tractor model. An on-line analysis of the data is used to determine if enough excitation is available for adaptation. A cascaded Kalman Filter is presented to estimate the slope of the DC gain of the steer angle to yaw rate transfer function, MDC, with respect to velocity. An estimator also provides faster updates of position. From the on-line estimate of MDC, the controller gains are scheduled based on a lookup table of predetermined values that were calculated from system identification tests. The sensitivity of the controller to model simplifications, incorrect velocities, and MDC estimate errors are investigated. The accuracy of the estimated MDC due to neglected dynamics and the rate of convergence is shown. A simulation is used to show the errors that can be induced in the position estimator by the GPS delay. The yaw rate estimator is designed for fixed point math using a square root covariance filter. Experimental and simulation results are provided which show the validity of the MDC estimate. Finally, experimental results which show that the accuracy changes little as a result of hitch loading and velocity are presented and discussed.

@unpublished{flenniken_modeling_2005,
	type = {Thesis},
	title = {Modeling {Inertial} {Measurement} {Units} and {Anlyzing} the {Effect} of {Their} {Errors} in {Navigation} {Applications}},
	url = {https://etd.auburn.edu//handle/10415/329},
	abstract = {In this thesis, a simple model that statistically represents an Inertial Measurement Unit (IMU) output has been studied.  This model is then expanded to produce a model that incorporates terms that account for errors associated with high dynamics.  Several techniques are used to determine the error statistics of the IMU model and categorize the performance of the IMU.  These techniques include Allan variance charts, Monte Carlo simulations and autocorrelation functions.  Equations for the position, velocity and heading error in a two and six degree of freedom system are developed.  These analytical equations for the error growth are then verified using Monte Carlo simulations.  Monte Carlo simulations are also used to compare the error bounds using both the simple model and high dynamic model.  A novel Kalman filter is developed to couple GPS with an inertial measurement unit in order to bound the error growth.  The Kalman filter estimates both a constant and drifting bias.  The error bounds on the position, velocity and heading state estimations are compared to the error bounds in the simple model’s uncoupled case.  The framework formulated from these models is intended as an aid for understanding the effects that the different error sources have on position, velocity, and heading calculations.  With this information it is possible to determine the correct inertial measurement unit with identified error characteristics for a specific application.},
	language = {en\_US},
	urldate = {2024-06-25},
	author = {Flenniken, Warren},
	month = dec,
	year = {2005},
	note = {Accepted: 2008-09-09T21:16:34Z},
}

In this thesis, a simple model that statistically represents an Inertial Measurement Unit (IMU) output has been studied. This model is then expanded to produce a model that incorporates terms that account for errors associated with high dynamics. Several techniques are used to determine the error statistics of the IMU model and categorize the performance of the IMU. These techniques include Allan variance charts, Monte Carlo simulations and autocorrelation functions. Equations for the position, velocity and heading error in a two and six degree of freedom system are developed. These analytical equations for the error growth are then verified using Monte Carlo simulations. Monte Carlo simulations are also used to compare the error bounds using both the simple model and high dynamic model. A novel Kalman filter is developed to couple GPS with an inertial measurement unit in order to bound the error growth. The Kalman filter estimates both a constant and drifting bias. The error bounds on the position, velocity and heading state estimations are compared to the error bounds in the simple model’s uncoupled case. The framework formulated from these models is intended as an aid for understanding the effects that the different error sources have on position, velocity, and heading calculations. With this information it is possible to determine the correct inertial measurement unit with identified error characteristics for a specific application.

@unpublished{whitehead_study_2005,
	type = {Thesis},
	title = {A {Study} of the {Properties} {That} {Influence} {Vehicle} {Rollover} {Propensity}},
	url = {https://etd.auburn.edu//handle/10415/379},
	abstract = {In this thesis, a vehicle’s load condition is varied to investigate its impact on roll stability and a stability threshold is derived empirically using vehicle simulation.  A vehicle model is developed and simulated using MATLAB.  Experiments performed by the National Highway Transportation and Safety Administration (NHTSA), are used to validate the simulation.  Data from these experiments is also used to validate a stability threshold developed from the simulation.  
Scaled passenger vehicles in conjunction with computer simulation have proven to be a valuable tool in determining rollover propensity.  The stability threshold is also validated by scaled vehicle experiments.  This is made possible with the lower cost and increased safety of using a scaled vehicle versus full size passenger vehicles.  A simple electronic stability control (ESC) is then developed to keep the scaled vehicle within the stability threshold.  The ESC is tested using varying vehicle properties with a constant vehicle model to see how these property changes affect the ESC’s effectiveness to prevent rollover.  The ESC is then implemented with an Intelligent Vehicle Model (IVM) which updates the controller’s vehicle model as vehicle properties such as loading conditions change.  It is shown that an IVM greatly increases the success of ESC in keeping the vehicle in the stability region.},
	language = {en\_US},
	urldate = {2024-06-25},
	author = {Whitehead, Randall},
	month = dec,
	year = {2005},
	note = {Accepted: 2008-09-09T21:17:11Z},
}

In this thesis, a vehicle’s load condition is varied to investigate its impact on roll stability and a stability threshold is derived empirically using vehicle simulation. A vehicle model is developed and simulated using MATLAB. Experiments performed by the National Highway Transportation and Safety Administration (NHTSA), are used to validate the simulation. Data from these experiments is also used to validate a stability threshold developed from the simulation. Scaled passenger vehicles in conjunction with computer simulation have proven to be a valuable tool in determining rollover propensity. The stability threshold is also validated by scaled vehicle experiments. This is made possible with the lower cost and increased safety of using a scaled vehicle versus full size passenger vehicles. A simple electronic stability control (ESC) is then developed to keep the scaled vehicle within the stability threshold. The ESC is tested using varying vehicle properties with a constant vehicle model to see how these property changes affect the ESC’s effectiveness to prevent rollover. The ESC is then implemented with an Intelligent Vehicle Model (IVM) which updates the controller’s vehicle model as vehicle properties such as loading conditions change. It is shown that an IVM greatly increases the success of ESC in keeping the vehicle in the stability region.

@inproceedings{anderson_estimation_2005,
	title = {Estimation of tire cornering stiffness using {GPS} to improve model based estimation of vehicle states},
	url = {https://ieeexplore.ieee.org/document/1505203/;jsessionid=0F91C6D6832D95F2F8ED5EE016D4DD48},
	doi = {10.1109/IVS.2005.1505203},
	abstract = {This paper demonstrates a method of obtaining key vehicle states using GPS and INS measurements with an adaptive model based estimator. A dual antenna GPS attitude system is used to estimate tire cornering stiffness. This estimated parameter is updated in the estimator model to provide more accurate estimates of the vehicle states. The experimental results for the estimate of sideslip and yaw rate using the updated estimator model compare favorable to values predicted by the theoretical model.},
	urldate = {2024-06-20},
	booktitle = {{IEEE} {Proceedings}. {Intelligent} {Vehicles} {Symposium}, 2005.},
	author = {Anderson, R. and Bevly, D.M.},
	month = jun,
	year = {2005},
	note = {ISSN: 1931-0587},
	keywords = {Antenna measurements, Control systems, Global Positioning System, Goniometers, Gyroscopes, Predictive models, State estimation, Tires, Vehicles, Velocity measurement},
	pages = {801--806},
}

This paper demonstrates a method of obtaining key vehicle states using GPS and INS measurements with an adaptive model based estimator. A dual antenna GPS attitude system is used to estimate tire cornering stiffness. This estimated parameter is updated in the estimator model to provide more accurate estimates of the vehicle states. The experimental results for the estimate of sideslip and yaw rate using the updated estimator model compare favorable to values predicted by the theoretical model.

@inproceedings{travis_corridor_2005,
	title = {Corridor navigation with a {LiDAR}/{INS} {Kalman} filter solution},
	url = {https://ieeexplore.ieee.org/document/1505126/;jsessionid=766C78FF7F8A59904B86C4EB6842AE59},
	doi = {10.1109/IVS.2005.1505126},
	abstract = {Autonomous capability requires reliable and robust navigation solutions in multiple environments. GPS has become an effective tool but is not suitable for all environments. Laser scanners are quickly making their presence known in the navigation field and are proven to have a variety of uses. This paper investigates the use of LiDAR within an indoor corridor environment (i.e. hallway) to update IMU measurements. The LiDAR is combined with an IMU in a Kalman filter to produce estimates of vehicle velocity, heading, lateral error, and sensor biases. It is shown how this combination is effective in providing accurate state estimates while removing sensor errors due to noise and bias.},
	urldate = {2024-06-20},
	booktitle = {{IEEE} {Proceedings}. {Intelligent} {Vehicles} {Symposium}, 2005.},
	author = {Travis, W. and Simmons, A.T. and Bevly, D.M.},
	month = jun,
	year = {2005},
	note = {ISSN: 1931-0587},
	keywords = {Filters, Global Positioning System, Land vehicles, Laser radar, Micromechanical devices, Navigation, Remotely operated vehicles, Robustness, State estimation, Working environment noise},
	pages = {343--348},
}

Autonomous capability requires reliable and robust navigation solutions in multiple environments. GPS has become an effective tool but is not suitable for all environments. Laser scanners are quickly making their presence known in the navigation field and are proven to have a variety of uses. This paper investigates the use of LiDAR within an indoor corridor environment (i.e. hallway) to update IMU measurements. The LiDAR is combined with an IMU in a Kalman filter to produce estimates of vehicle velocity, heading, lateral error, and sensor biases. It is shown how this combination is effective in providing accurate state estimates while removing sensor errors due to noise and bias.

@inproceedings{behringer_rascal_2005,
	title = {{RASCAL} - an autonomous ground vehicle for desert driving in the {DARPA} {Grand} {Challenge} 2005},
	url = {https://ieeexplore.ieee.org/document/1520123/;jsessionid=17454A5F511C46DDA3DCDDD5225A80E0},
	abstract = {The DARPA Grand Challenge is a competition of autonomous ground vehicles in the Mojave desert, with a prize of},
	urldate = {2024-06-20},
	booktitle = {Proceedings. 2005 {IEEE} {Intelligent} {Transportation} {Systems}, 2005.},
	author = {Behringer, R. and Travis, W. and Daily, R. and Bevly, D. and Kubinger, W. and Herzner, W. and Fehlberg, V.},
	year = {2005},
	pages = {644--649},
}

The DARPA Grand Challenge is a competition of autonomous ground vehicles in the Mojave desert, with a prize of

@inproceedings{iv_characterization_2005,
	title = {Characterization of {Various} {IMU} {Error} {Sources} and the {Effect} on {Navigation} {Performance}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=6292},
	abstract = {This paper introduces a simple model for modeling inertial sensors and expands on this model to incorporate terms that model the errors associated with high dynamics. The paper uses the techniques of Allan Variance Charts, Monte Carlo Simulations, and Autocorrelation functions to characterize sensors through identification of the error statistics. The error growth of the position and heading navigation solution for two and six degree of freedom scenarios using static error parameters is developed. Analytical expressions for the error growth with wide-band noise are presented and used as an error baseline for investigating the effects of sensor drift, or walking bias. Experimental data is used to validate the error growth bounds in both scenarios. An advanced sensor model is developed for both an accelerometer and gyro with an explanation of the effects of the dynamic error parameters. A simple rocket trajectory simulation is used to illustrate the adverse effects of high dynamic sensor errors when dead-reckoning with a tactile-grade IMU. Analysis of the advanced model is concluded with an investigation into the relative effect of each error parameter on the trajectory target.},
	language = {en},
	urldate = {2024-06-20},
	author = {Iv, Warren S. Flenniken and Wall, John H. and Bevly, David M.},
	month = sep,
	year = {2005},
	pages = {967--978},
}

This paper introduces a simple model for modeling inertial sensors and expands on this model to incorporate terms that model the errors associated with high dynamics. The paper uses the techniques of Allan Variance Charts, Monte Carlo Simulations, and Autocorrelation functions to characterize sensors through identification of the error statistics. The error growth of the position and heading navigation solution for two and six degree of freedom scenarios using static error parameters is developed. Analytical expressions for the error growth with wide-band noise are presented and used as an error baseline for investigating the effects of sensor drift, or walking bias. Experimental data is used to validate the error growth bounds in both scenarios. An advanced sensor model is developed for both an accelerometer and gyro with an explanation of the effects of the dynamic error parameters. A simple rocket trajectory simulation is used to illustrate the adverse effects of high dynamic sensor errors when dead-reckoning with a tactile-grade IMU. Analysis of the advanced model is concluded with an investigation into the relative effect of each error parameter on the trajectory target.

@inproceedings{travis_navigation_2005,
	title = {Navigation {Errors} {Introduced} {By} {Ground} {Vehicle} {Dynamics}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=6221},
	abstract = {An analysis of navigational accuracy when influenced by ground vehicle dynamics is presented. Tests beds outfitted with various sensor suites were used to collect data when normal and extreme driving maneuvers are executed. The data was run through an extended Kalman filter to produce a navigation solution. The Kalman filter inputs varied on each test bed, using both automotive and tactical grade Inertial Measurement Units (IMU). The position, velocity, and course measurements were obtained from a DGPS unit mounted on the vehicles and used as a truth measurement when exploring dead reckoning error. Additional measurements, such as wheel speed, radar speed, and magnetometer heading, were added to improve the robustness and reliability of the solution. The results of the work show the effect of both longitudinal and lateral vehicle slip on the navigation solution. In addition, the attempt of the various sensors to correct the errors is investigated.},
	language = {en},
	urldate = {2024-06-20},
	author = {Travis, William and Bevly, David M.},
	month = sep,
	year = {2005},
	pages = {302--310},
}

An analysis of navigational accuracy when influenced by ground vehicle dynamics is presented. Tests beds outfitted with various sensor suites were used to collect data when normal and extreme driving maneuvers are executed. The data was run through an extended Kalman filter to produce a navigation solution. The Kalman filter inputs varied on each test bed, using both automotive and tactical grade Inertial Measurement Units (IMU). The position, velocity, and course measurements were obtained from a DGPS unit mounted on the vehicles and used as a truth measurement when exploring dead reckoning error. Additional measurements, such as wheel speed, radar speed, and magnetometer heading, were added to improve the robustness and reliability of the solution. The results of the work show the effect of both longitudinal and lateral vehicle slip on the navigation solution. In addition, the attempt of the various sensors to correct the errors is investigated.

@inproceedings{pearson_comparison_2005,
	address = {Orlando, Florida, USA},
	title = {Comparison of {Analytical} and {Empirical} {Models} to {Capture} {Variations} in {Off}-{Road} {Vehicle} {Dynamics}},
	isbn = {978-0-7918-4215-7},
	url = {https://asmedigitalcollection.asme.org/IMECE/proceedings/IMECE2005/42150/201/308909},
	doi = {10.1115/IMECE2005-81660},
	abstract = {This paper develops two analytical models that describe the yaw dynamics of a farm tractor and can be used to design or improve steering control algorithms for the tractor. These models are verified against empirical data. The particular dynamics described are the motions from steering angle to yaw rate. A John Deere 8420 tractor, outfitted with inertial sensors and controlled through a PC-104 form factor computer, was used for experimental validation. Conditions including different implements at varying depths, as would normally be found on a farm, were tested. This paper presents the development of the analytical models, validates them against empirical data, and gives trends on how the model parameters change for different configurations.},
	urldate = {2024-06-20},
	booktitle = {Design {Engineering}, {Parts} {A} and {B}},
	publisher = {ASMEDC},
	author = {Pearson, Paul J. and Bevly, David M.},
	month = jan,
	year = {2005},
	pages = {201--208},
}

This paper develops two analytical models that describe the yaw dynamics of a farm tractor and can be used to design or improve steering control algorithms for the tractor. These models are verified against empirical data. The particular dynamics described are the motions from steering angle to yaw rate. A John Deere 8420 tractor, outfitted with inertial sensors and controlled through a PC-104 form factor computer, was used for experimental validation. Conditions including different implements at varying depths, as would normally be found on a farm, were tested. This paper presents the development of the analytical models, validates them against empirical data, and gives trends on how the model parameters change for different configurations.

@inproceedings{gartley_-line_2005,
	address = {Orlando, Florida, USA},
	title = {On-{Line} {Adaptive} {Control} of a {Farm} {Tractor} by {Compensation} of {Parameter} {Variations}},
	isbn = {978-0-7918-4216-4},
	url = {https://asmedigitalcollection.asme.org/IMECE/proceedings/IMECE2005/42169/977/311905},
	doi = {10.1115/IMECE2005-81344},
	abstract = {An adaptive control technique for the control of a farm tractor during low levels of excitation and at low velocities is presented. An analysis of the data is conducted to determine when it is safe to adapt. A cascaded Kalman Filter is presented to estimate the slope of the DC gain of the steer angle to yaw rate transfer function with respect to velocity and to provide faster updates of position. Given this parameter, the controller gains will be scheduled based on a lookup table of predetermined values that were calculated from system identification tests.},
	urldate = {2024-06-20},
	booktitle = {Dynamic {Systems} and {Control}, {Parts} {A} and {B}},
	publisher = {ASMEDC},
	author = {Gartley, Evan R. and Bevly, David M.},
	month = jan,
	year = {2005},
	pages = {977--985},
}

An adaptive control technique for the control of a farm tractor during low levels of excitation and at low velocities is presented. An analysis of the data is conducted to determine when it is safe to adapt. A cascaded Kalman Filter is presented to estimate the slope of the DC gain of the steer angle to yaw rate transfer function with respect to velocity and to provide faster updates of position. Given this parameter, the controller gains will be scheduled based on a lookup table of predetermined values that were calculated from system identification tests.

@inproceedings{heffernan_validation_2005,
	address = {Orlando, Florida, USA},
	title = {Validation of {Longitudinal} {Vehicle} {Estimation} {Techniques} on a {Heavy} {Truck} {Test}-{Bed}},
	isbn = {978-0-7918-4216-4},
	url = {https://asmedigitalcollection.asme.org/IMECE/proceedings/IMECE2005/42169/563/311857},
	doi = {10.1115/IMECE2005-81901},
	abstract = {Commercial vehicles display a large variation in their parameters, and due to many current trends in vehicle control systems, identifying these parameters has been the subject of much research. Using the National Center for Asphalt Technology’s test track and instrumented Freightliner vehicles as a test bed, this paper sets out to provide analysis of real world and simulated estimation results and explore how sensor accuracies can degrade these results. Various vehicle parameters are identified using both the existing test conditions of the facility and simulated data. The estimation accuracy and performance are then analyzed for validation and use in other vehicle design arenas.},
	urldate = {2024-06-20},
	booktitle = {Dynamic {Systems} and {Control}, {Parts} {A} and {B}},
	publisher = {ASMEDC},
	author = {Heffernan, Matthew E. and Bevly, David},
	month = jan,
	year = {2005},
	pages = {563--569},
}

Commercial vehicles display a large variation in their parameters, and due to many current trends in vehicle control systems, identifying these parameters has been the subject of much research. Using the National Center for Asphalt Technology’s test track and instrumented Freightliner vehicles as a test bed, this paper sets out to provide analysis of real world and simulated estimation results and explore how sensor accuracies can degrade these results. Various vehicle parameters are identified using both the existing test conditions of the facility and simulated data. The estimation accuracy and performance are then analyzed for validation and use in other vehicle design arenas.

@inproceedings{whitehead_esc_2005,
	address = {Orlando, Florida, USA},
	title = {{ESC} {Effectiveness} {During} {Property} {Variations} on {Scaled} {Vehicles}},
	isbn = {978-0-7918-4215-7},
	url = {https://asmedigitalcollection.asme.org/IMECE/proceedings/IMECE2005/42150/233/308832},
	doi = {10.1115/IMECE2005-82558},
	abstract = {Scaled passenger vehicles in conjunction with computer simulation have proven to be a valuable tool in determining rollover propensity. In this study, vehicle properties are varied to see their impact on roll stability and a stability threshold is derived empirically using simulation. The stability threshold is validated by scaled vehicle experiments. This is made possible with the lower cost and increased safety of using a scaled vehicle versus full size passenger vehicles. A simple electronic stability control (ESC) is then developed to keep the scaled vehicle within the stability threshold. The ESC is tested using varying vehicle properties with a constant vehicle model to see how these property changes affect the ESC’s effectiveness to prevent rollover. The ESC is then implemented with an Intelligent Vehicle Model (IVM) which updates the controller’s vehicle model as vehicle properties such as loading conditions change. This study shows that an IVM greatly increases the success of ESC in keeping the vehicle in the stability region.},
	urldate = {2024-06-20},
	booktitle = {Design {Engineering}, {Parts} {A} and {B}},
	publisher = {ASMEDC},
	author = {Whitehead, Randy and Clark, Ben and Bevly, David M.},
	month = jan,
	year = {2005},
	pages = {233--241},
}

Scaled passenger vehicles in conjunction with computer simulation have proven to be a valuable tool in determining rollover propensity. In this study, vehicle properties are varied to see their impact on roll stability and a stability threshold is derived empirically using simulation. The stability threshold is validated by scaled vehicle experiments. This is made possible with the lower cost and increased safety of using a scaled vehicle versus full size passenger vehicles. A simple electronic stability control (ESC) is then developed to keep the scaled vehicle within the stability threshold. The ESC is tested using varying vehicle properties with a constant vehicle model to see how these property changes affect the ESC’s effectiveness to prevent rollover. The ESC is then implemented with an Intelligent Vehicle Model (IVM) which updates the controller’s vehicle model as vehicle properties such as loading conditions change. This study shows that an IVM greatly increases the success of ESC in keeping the vehicle in the stability region.

@book{american_society_of_mechanical_engineers_proceedings_2005,
	address = {New York, N.Y},
	series = {{DSC}},
	title = {Proceedings of the {ASME} {Dynamic} {Systems} and {Control} {Division}--2005: presented at 2005 {ASME} {International} {Mechanical} {Engineering} {Congress} and {Exposition}, {November} 5-11, 2005, {Orlando}, {Florida}, {USA}},
	isbn = {9780791842164},
	shorttitle = {Proceedings of the {ASME} {Dynamic} {Systems} and {Control} {Division}--2005},
	number = {vol. 74},
	publisher = {American Society of Mechanical Engineers},
	editor = {{American Society of Mechanical Engineers}},
	year = {2005},
	note = {OCLC: ocm65180503},
	keywords = {Automatic control, Congresses, Control theory, Intelligent control systems},
}

@inproceedings{hamm_simulated_2005,
	title = {Simulated {Performance} {Analysis} of a {Composite} {Vector} {Tracking} and {Navigation} {Filter}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=6241},
	abstract = {This paper presents an alternative GPS signal tracking method which uses an extended Kalman-Bucy filter in place of traditional independent, parallel tracking loops. Furthermore, this method is extended into a combined tracking and navigation filter coupled with inertial aiding. This approach reduces filter design complexity significantly and allows for optimal navigation performance in a variety of conditions. Specifically, the proposed method is demonstrated under high dynamics while experiencing significant levels of jamming. A simulation in a single-axis configuration was used to compare the proposed method to an existing aided fixed-gain method to ascertain the expected level of anti-jam performance as well as immunity to dynamic stress. Results from this simulation indicate a nominal expected positioning performance improvement of 5 meters with improvements of up to 25 meters in some cases. A simulation comparing IMU’s of differing grades was also run to ascertain the proposed method’s dependence upon inertial sensor quality.},
	language = {en},
	urldate = {2024-06-20},
	author = {Hamm, Christopher R. and Bevly, David M.},
	month = sep,
	year = {2005},
	pages = {478--487},
}

This paper presents an alternative GPS signal tracking method which uses an extended Kalman-Bucy filter in place of traditional independent, parallel tracking loops. Furthermore, this method is extended into a combined tracking and navigation filter coupled with inertial aiding. This approach reduces filter design complexity significantly and allows for optimal navigation performance in a variety of conditions. Specifically, the proposed method is demonstrated under high dynamics while experiencing significant levels of jamming. A simulation in a single-axis configuration was used to compare the proposed method to an existing aided fixed-gain method to ascertain the expected level of anti-jam performance as well as immunity to dynamic stress. Results from this simulation indicate a nominal expected positioning performance improvement of 5 meters with improvements of up to 25 meters in some cases. A simulation comparing IMU’s of differing grades was also run to ascertain the proposed method’s dependence upon inertial sensor quality.

@inproceedings{behringer_development_2004,
	title = {{DEVELOPMENT} {OF} {AN} {AUTONOMOUS} {VEHICLE} {FOR} {THE} {DARPA} {GRAND} {CHALLENGE}},
	language = {en},
	author = {Behringer, R and Gregory, B and Sundareswaran, V and Addison, R and Elsley, R and Guthmiller, W and Daily, R and Bevly, D and Reinhart, C},
	year = {2004},
}

@inproceedings{whitehead_study_2004,
	address = {Warrendale, PA},
	title = {A {Study} of the {Effect} of {Various} {Vehicle} {Properties} on {Rollover} {Propensity}},
	url = {https://www.sae.org/publications/technical-papers/content/2004-01-2094/},
	abstract = {This paper investigates the effect of various vehicle parameters on rollover propensity using computer simulation. The computer simulation’s accuracy is verified by comparing it to experimental data from NHTSA’s Phase IV testing on rollover of passenger vehicles. The vehicle model used in the simula},
	language = {English},
	urldate = {2024-06-20},
	publisher = {SAE Technical Paper},
	author = {Whitehead, Randy and Travis, William and Bevly, David M. and Flowers, George},
	month = may,
	year = {2004},
	doi = {10.4271/2004-01-2094},
}

This paper investigates the effect of various vehicle parameters on rollover propensity using computer simulation. The computer simulation’s accuracy is verified by comparing it to experimental data from NHTSA’s Phase IV testing on rollover of passenger vehicles. The vehicle model used in the simula

@inproceedings{travis_using_2004,
	title = {Using scaled vehicles to investigate the influence of various properties on rollover propensity},
	volume = {4},
	url = {https://ieeexplore.ieee.org/document/1384431/;jsessionid=271056D326503AEA01572F1C61287742},
	doi = {10.23919/ACC.2004.1384431},
	abstract = {Quantifying a vehicle's rollover propensity is a complex task and one that is of major concern to vehicle dynamicists. This research effort illustrates how a scaled vehicle can be used in determining vehicle properties that influence rollover propensity. A two-axis inertial measurement unit (IMU) and a global positioning system (GPS) unit are mounted to a scaled vehicle to measure its dynamic behavior. Vehicle maneuvers are performed on a test track and a computer vehicle simulation is used to compare the experimental results from the scaled vehicle with passenger vehicle dynamics. The simulation was able to accurately predict the dynamic behavior of the scaled vehicle, providing a link between full size vehicle roll dynamics and scale vehicle roll dynamics.},
	urldate = {2024-06-20},
	booktitle = {Proceedings of the 2004 {American} {Control} {Conference}},
	author = {Travis, W.E. and Whitehead, R.J. and Bevly, D.M. and Flowers, G.T.},
	month = jun,
	year = {2004},
	note = {ISSN: 0743-1619},
	keywords = {Computational modeling, Global Positioning System, Mechanical engineering, Nonlinear dynamical systems, Road vehicles, Stability, US Department of Transportation, Vehicle crash testing, Vehicle dynamics, Vehicle safety},
	pages = {3381--3386 vol.4},
}

Quantifying a vehicle's rollover propensity is a complex task and one that is of major concern to vehicle dynamicists. This research effort illustrates how a scaled vehicle can be used in determining vehicle properties that influence rollover propensity. A two-axis inertial measurement unit (IMU) and a global positioning system (GPS) unit are mounted to a scaled vehicle to measure its dynamic behavior. Vehicle maneuvers are performed on a test track and a computer vehicle simulation is used to compare the experimental results from the scaled vehicle with passenger vehicle dynamics. The simulation was able to accurately predict the dynamic behavior of the scaled vehicle, providing a link between full size vehicle roll dynamics and scale vehicle roll dynamics.

@inproceedings{anderson_estimation_2004,
	title = {Estimation of slip angles using a model based estimator and {GPS}},
	volume = {3},
	url = {https://ieeexplore.ieee.org/document/1383774/;jsessionid=08EFFBA0BED0504BCE3CD0264B7D0F3D},
	doi = {10.23919/ACC.2004.1383774},
	abstract = {This paper demonstrates a method for estimating key vehicle states and sensor biases using Global Positioning System (GPS) and an Internal Navigation System (INS). Two Kalman filters, a model based filter and a kinematic filter, are used to integrate the INS sensors with GPS heading and velocity to provide a high update rate of the vehicle states and sensor biases. Additional key vehicle parameters, such as tire-cornering stiffness, are identified and used to correct the model based estimator. The vehicle estimated states compare favorable with values predicted with a theoretical model.},
	urldate = {2024-06-20},
	booktitle = {Proceedings of the 2004 {American} {Control} {Conference}},
	author = {Anderson, R. and Bevly, D.M.},
	month = jun,
	year = {2004},
	note = {ISSN: 0743-1619},
	keywords = {Bicycles, Equations, Filters, Global Positioning System, Kinematics, Roads, State estimation, Tires, Vehicles, Velocity measurement},
	pages = {2122--2127 vol.3},
}

This paper demonstrates a method for estimating key vehicle states and sensor biases using Global Positioning System (GPS) and an Internal Navigation System (INS). Two Kalman filters, a model based filter and a kinematic filter, are used to integrate the INS sensors with GPS heading and velocity to provide a high update rate of the vehicle states and sensor biases. Additional key vehicle parameters, such as tire-cornering stiffness, are identified and used to correct the model based estimator. The vehicle estimated states compare favorable with values predicted with a theoretical model.

@inproceedings{plumlee_control_2004,
	title = {Control of a ground vehicle using quadratic programming based control allocation techniques},
	volume = {5},
	url = {https://ieeexplore.ieee.org/abstract/document/1384055},
	doi = {10.23919/ACC.2004.1384055},
	abstract = {This paper examines the use of control allocation techniques for the control of multiple inputs to a ground vehicle to track a desired yaw rate trajectory while minimizing vehicle sideslip. The proposed controller uses quadratic programming accompanied by linear quadratic regulator gains designed around a linear vehicle model to arrive at a combination of vehicle commands. Several failure scenarios are examined and the results for two different quadratic programming approaches are presented along with a discussion of the advantages each method has to offer.},
	urldate = {2024-06-20},
	booktitle = {Proceedings of the 2004 {American} {Control} {Conference}},
	author = {Plumlee, J.H. and Bevly, D.M. and Hodel, A.S.},
	month = jun,
	year = {2004},
	note = {ISSN: 0743-1619},
	keywords = {Aerospace safety, Land vehicles, Mechanical engineering, Optimal control, Quadratic programming, Regulators, Road vehicles, Torque control, Trajectory, Vehicle safety},
	pages = {4704--4709 vol.5},
}

This paper examines the use of control allocation techniques for the control of multiple inputs to a ground vehicle to track a desired yaw rate trajectory while minimizing vehicle sideslip. The proposed controller uses quadratic programming accompanied by linear quadratic regulator gains designed around a linear vehicle model to arrive at a combination of vehicle commands. Several failure scenarios are examined and the results for two different quadratic programming approaches are presented along with a discussion of the advantages each method has to offer.

@inproceedings{hamm_comparative_2004,
	title = {Comparative {Performance} {Analysis} of {Aided} {Carrier} {Tracking} {Loop} {Algorithms} in {High} {Noise}/{High} {Dynamic} {Environments}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=5728},
	abstract = {Five different approaches to GPS carrier tracking loops were compared in a simulated environment for their performance against a high dynamic/high noise environment. The loops tested were a second order loop, a third order loop, an aided second order loop, a Kalman filter, and an adaptive order loop. The simulation varied the jammer-to-signal (J/S) while holding inertial quality and acceleration profile constant. Similarly, the acceleration profile was varied with other factors constant. In a final test, the quality of inertial measurements was varied such as to resemble various qualities of available sensors and the other parameters held constant. Under high dynamics and high noise, the aided second order tracking loop provided the least amount of phase error. The adaptive order provides a good measured response under these configurations and does not requiring highly accurate accelerometer measurements.},
	language = {en},
	urldate = {2024-06-20},
	author = {Hamm, Christopher R. and Iv, Warren S. Flenniken and Bevly, David M. and Lawerence, Daniel E.},
	month = sep,
	year = {2004},
	pages = {523--532},
}

Five different approaches to GPS carrier tracking loops were compared in a simulated environment for their performance against a high dynamic/high noise environment. The loops tested were a second order loop, a third order loop, an aided second order loop, a Kalman filter, and an adaptive order loop. The simulation varied the jammer-to-signal (J/S) while holding inertial quality and acceleration profile constant. Similarly, the acceleration profile was varied with other factors constant. In a final test, the quality of inertial measurements was varied such as to resemble various qualities of available sensors and the other parameters held constant. Under high dynamics and high noise, the aided second order tracking loop provided the least amount of phase error. The adaptive order provides a good measured response under these configurations and does not requiring highly accurate accelerometer measurements.

@inproceedings{machiel_van_der_loos_split-crank_2002,
	title = {A split-crank, servomotor-controlled bicycle ergometer design for studies in human biomechanics},
	volume = {2},
	url = {https://ieeexplore.ieee.org/document/1043952/;jsessionid=CA8D573AB267CFBF18A54C998DCA390C},
	doi = {10.1109/IRDS.2002.1043952},
	abstract = {This paper presents a novel computer-controlled bicycle ergometer, the TiltCycle, for use in human biomechanics studies of pedaling. The TiltCycle has a tilting (reclining) seat and backboard, a split crank to isolate the left and right loads to the feet of the cyclist, and two belt-driven, computer-controller motors to provide both assistance and resistance loads. Sensors measure the kinematics and force production of the pedaling work performed, as well as goniometer and electromyography signals from the lower limbs. The technical description includes the mechanical design, low-level software and control algorithms designed for studies in human lower-limb biomechanics and bilateral coordination, and concludes with validation testing and system identification results.},
	urldate = {2024-06-20},
	booktitle = {{IEEE}/{RSJ} {International} {Conference} on {Intelligent} {Robots} and {Systems}},
	author = {Machiel Van der Loos, H.F. and Kautz, S.A. and Schwandt, D.F. and Anderson, J. and Chen, G. and Bevly, D.M.},
	month = sep,
	year = {2002},
	keywords = {Algorithm design and analysis, Bicycles, Biomechanics, Biosensors, Electrical resistance measurement, Force measurement, Humans, Immune system, Kinematics, Mechanical sensors},
	pages = {1409--1414 vol.2},
}

This paper presents a novel computer-controlled bicycle ergometer, the TiltCycle, for use in human biomechanics studies of pedaling. The TiltCycle has a tilting (reclining) seat and backboard, a split crank to isolate the left and right loads to the feet of the cyclist, and two belt-driven, computer-controller motors to provide both assistance and resistance loads. Sensors measure the kinematics and force production of the pedaling work performed, as well as goniometer and electromyography signals from the lower limbs. The technical description includes the mechanical design, low-level software and control algorithms designed for studies in human lower-limb biomechanics and bilateral coordination, and concludes with validation testing and system identification results.

@inproceedings{bevly_integrating_2001,
	title = {Integrating {INS} sensors with {GPS} velocity measurements for continuous estimation of vehicle sideslip and tire cornering stiffness},
	volume = {1},
	url = {https://ieeexplore.ieee.org/document/945508/;jsessionid=C8FDC1E9EC068F90EAB7F429830C02A3},
	doi = {10.1109/ACC.2001.945508},
	abstract = {This paper details a unique method for measuring key vehicle states-body sideslip angle, and tire sideslip angle-using GPS velocity information in conjunction with other sensors. A method for integrating inertial navigation system (INS) sensors with GPS measurements to provide higher update rate estimates of the vehicle states is presented. Additionally, it is shown that the tire sideslip estimates can be used to estimate the tire cornering stiffnesses. The experimental results for the GPS velocity-based sideslip angle measurement and cornering stiffness estimates compare favorably to theoretical predictions, suggesting that this technique has merit for future implementation in vehicle safety systems.},
	urldate = {2024-06-20},
	booktitle = {Proceedings of the 2001 {American} {Control} {Conference}. ({Cat}. {No}.{01CH37148})},
	author = {Bevly, D.M. and Sheridan, R. and Gerdes, J.C.},
	month = jun,
	year = {2001},
	note = {ISSN: 0743-1619},
	keywords = {Automatic control, Control systems, Global Positioning System, Mechanical sensors, Sensor systems, Stability, State estimation, Tires, Vehicles, Velocity measurement},
	pages = {25--30 vol.1},
}

This paper details a unique method for measuring key vehicle states-body sideslip angle, and tire sideslip angle-using GPS velocity information in conjunction with other sensors. A method for integrating inertial navigation system (INS) sensors with GPS measurements to provide higher update rate estimates of the vehicle states is presented. Additionally, it is shown that the tire sideslip estimates can be used to estimate the tire cornering stiffnesses. The experimental results for the GPS velocity-based sideslip angle measurement and cornering stiffness estimates compare favorably to theoretical predictions, suggesting that this technique has merit for future implementation in vehicle safety systems.

@inproceedings{bevly_yaw_2000,
	address = {Orlando, Florida, USA},
	title = {Yaw {Dynamic} {Modeling} for {Improved} {High} {Speed} {Control} of a {Farm} {Tractor}},
	isbn = {978-0-7918-2664-5},
	url = {https://asmedigitalcollection.asme.org/IMECE/proceedings/IMECE2000/26645/551/1126579},
	doi = {10.1115/IMECE2000-2347},
	abstract = {Abstract 
            This paper presents the system identification of a farm tractor in order to improve automatic control at higher speeds and understand controller limitations from neglecting the yaw dynamics. Yaw dynamic models are developed for multiple speeds to show the effect of velocity on the model. The identified modeled yaw dynamics do not resemble any traditional analytical models. Additionally, the effect of velocity on the closed loop bandwidth of the controller for a given set of LQR controller weights is presented. Results are given that validate that as the closed loop bandwidth of LQR control weights approaches the regime of the unmodelled yaw dynamics, the controller can go unstable. Finally results show an improvement of the lateral tracking error (with a decrease in control effort) using the system identification model.},
	urldate = {2024-06-20},
	booktitle = {Dynamic {Systems} and {Control}: {Volume} 1},
	publisher = {American Society of Mechanical Engineers},
	author = {Bevly, David M. and Gerdes, J. Christian and Parkinson, Bradford W.},
	month = nov,
	year = {2000},
	pages = {551--557},
}

Abstract This paper presents the system identification of a farm tractor in order to improve automatic control at higher speeds and understand controller limitations from neglecting the yaw dynamics. Yaw dynamic models are developed for multiple speeds to show the effect of velocity on the model. The identified modeled yaw dynamics do not resemble any traditional analytical models. Additionally, the effect of velocity on the closed loop bandwidth of the controller for a given set of LQR controller weights is presented. Results are given that validate that as the closed loop bandwidth of LQR control weights approaches the regime of the unmodelled yaw dynamics, the controller can go unstable. Finally results show an improvement of the lateral tracking error (with a decrease in control effort) using the system identification model.

@inproceedings{bevly_use_2000,
	title = {The use of {GPS} based velocity measurements for improved vehicle state estimation},
	volume = {4},
	url = {https://ieeexplore.ieee.org/document/878665/;jsessionid=8F3A70C64A353B3F0F7137E99D26B9EE},
	doi = {10.1109/ACC.2000.878665},
	abstract = {Details a method for measuring three key vehicle states-wheel slip, body sideslip angle, and tire sideslip angle-using GPS velocity information in conjunction with other sensors. Based on initial noise data obtained from the system components, a prediction of the accuracy of these new measurements is obtained. Subsequent experiments validate both the methodology for obtaining the measurements as well as the error analysis. The experimental results for the GPS velocity-based sideslip angle measurement compare favorably to theoretical predictions, suggesting that this technique has merit for future implementation in vehicle safety systems.},
	urldate = {2024-06-20},
	booktitle = {Proceedings of the 2000 {American} {Control} {Conference}. {ACC} ({IEEE} {Cat}. {No}.{00CH36334})},
	author = {Bevly, D.M. and Gerdes, J.C. and Wilson, C. and Zhang, Gengsheng},
	month = jun,
	year = {2000},
	note = {ISSN: 0743-1619},
	keywords = {Control systems, Error correction, Global Positioning System, Mechanical variables measurement, Stability, State estimation, Tires, Vehicles, Velocity measurement, Wheels},
	pages = {2538--2542 vol.4},
}

Details a method for measuring three key vehicle states-wheel slip, body sideslip angle, and tire sideslip angle-using GPS velocity information in conjunction with other sensors. Based on initial noise data obtained from the system components, a prediction of the accuracy of these new measurements is obtained. Subsequent experiments validate both the methodology for obtaining the measurements as well as the error analysis. The experimental results for the GPS velocity-based sideslip angle measurement compare favorably to theoretical predictions, suggesting that this technique has merit for future implementation in vehicle safety systems.

@inproceedings{bevly_action_2000,
	title = {Action module planning and its application to an experimental climbing robot},
	volume = {4},
	url = {https://ieeexplore.ieee.org/document/845356/;jsessionid=3F26DDD748836E0A552CB4218323DA23},
	doi = {10.1109/ROBOT.2000.845356},
	abstract = {This paper presents the application of an action module planning method to an experimental climbing robot named LIBRA. The method searches for a sequence of physically realizable actions, called action modules, to produce a plan for a given task. The search is performed with a hierarchical selection process that uses task and configuration filters to reduce the action module inventory to a reasonable search space. Then, a genetic algorithm search finds a sequence of actions that allows the robot to complete the task without violating any physical constraints. The results for the LIBRA climbing robot show the method is able to produce effective plans.},
	urldate = {2024-06-20},
	booktitle = {Proceedings 2000 {ICRA}. {Millennium} {Conference}. {IEEE} {International} {Conference} on {Robotics} and {Automation}. {Symposia} {Proceedings} ({Cat}. {No}.{00CH37065})},
	author = {Bevly, D.M. and Farritor, S. and Dubowsky, S.},
	month = apr,
	year = {2000},
	note = {ISSN: 1050-4729},
	keywords = {Actuators, Climbing robots, Ducts, Genetic algorithms, Mechanical engineering, Mobile robots, Motion planning, Orbital robotics, Robotic assembly, Robotics and automation},
	pages = {4009--4014 vol.4},
}

This paper presents the application of an action module planning method to an experimental climbing robot named LIBRA. The method searches for a sequence of physically realizable actions, called action modules, to produce a plan for a given task. The search is performed with a hierarchical selection process that uses task and configuration filters to reduce the action module inventory to a reasonable search space. Then, a genetic algorithm search finds a sequence of actions that allows the robot to complete the task without violating any physical constraints. The results for the LIBRA climbing robot show the method is able to produce effective plans.

@inproceedings{bevly_carrier-phase_2000,
	title = {Carrier-{Phase} {Differential} {GPS} for {Control} of a {Tractor} {Towed} {Implement}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=1643},
	abstract = {This paper explores the use of GPS position measurements on a tractor towed implement for position control of the implement. Several recent papers have focused on automatic steering control of farm vehicles using GPS. This paper extends that work to control a towed implement through automatic steering of a farm tractor. Many times implements are driven on curved trajectories, side-hills, or contours where the implement and tractor positions may differ. Additionally, some heavy implements will "pull heavy" to one side, creating a position bias. It would be advantageous to be able to control the actual position of the implement as opposed to the position of the tractor in these various circumstances. A simple analytical model is developed for the tractor/implement combination. The model is validated with experimental data using Carrier Phase Differential GPS position on the tractor as well as on the implement. A controller is then designed and implemented on the experimental system to control the position of the implement on a given path across the field. Experimental data is given to show the ability to control the position of the implement to within 10 cm of the desired path.},
	language = {en},
	urldate = {2024-06-20},
	author = {Bevly, David M. and Parkinson, Bradford},
	month = sep,
	year = {2000},
	pages = {2263--2268},
}

This paper explores the use of GPS position measurements on a tractor towed implement for position control of the implement. Several recent papers have focused on automatic steering control of farm vehicles using GPS. This paper extends that work to control a towed implement through automatic steering of a farm tractor. Many times implements are driven on curved trajectories, side-hills, or contours where the implement and tractor positions may differ. Additionally, some heavy implements will "pull heavy" to one side, creating a position bias. It would be advantageous to be able to control the actual position of the implement as opposed to the position of the tractor in these various circumstances. A simple analytical model is developed for the tractor/implement combination. The model is validated with experimental data using Carrier Phase Differential GPS position on the tractor as well as on the implement. A controller is then designed and implemented on the experimental system to control the position of the implement on a given path across the field. Experimental data is given to show the ability to control the position of the implement to within 10 cm of the desired path.

@article{bevly_incorporating_1999,
	title = {Incorporating {INS} with {Carrier}-{Phase} {Differential} {GPS} for {Automatic} {Steering} {Control} of a {Farm} {Tractor}},
	volume = {108},
	issn = {0096-736X},
	url = {https://www.jstor.org/stable/44723056},
	abstract = {This paper evaluates the use of a low cost inertial navigation system (INS) combined with Carrier-Phase Differential GPS (DGPS), to provide continuous position and attitude estimation for the control of a farm tractor. The INS system is used for dead-reckoning navigation to control the vehicle through short GPS outages. An Extended Kalman filter combines INS and Doppler radar measurements with cm-level Carrier-Phase Differential GPS measurements for continuous position and attitude estimation of the tractor. Results are given which verify the ability of the INS system to provide a heading accuracy within ±0.6° for control of the tractor. Additionally it is shown that the dead-reckoning system can provide position and attitude estimation to control the tractor to within ±0.3 meters through a short GPS outage.},
	urldate = {2024-06-20},
	journal = {SAE Transactions},
	author = {Bevly, David M. and Rekow, Andrew and Parkinson, Bradford},
	year = {1999},
	pages = {339--345},
}

This paper evaluates the use of a low cost inertial navigation system (INS) combined with Carrier-Phase Differential GPS (DGPS), to provide continuous position and attitude estimation for the control of a farm tractor. The INS system is used for dead-reckoning navigation to control the vehicle through short GPS outages. An Extended Kalman filter combines INS and Doppler radar measurements with cm-level Carrier-Phase Differential GPS measurements for continuous position and attitude estimation of the tractor. Results are given which verify the ability of the INS system to provide a heading accuracy within ±0.6° for control of the tractor. Additionally it is shown that the dead-reckoning system can provide position and attitude estimation to control the tractor to within ±0.3 meters through a short GPS outage.

@inproceedings{bevly_evaluation_1999,
	title = {Evaluation of a {Blended} {Dead} {Reckoning} and {Carrier} {Phase} {Differential} {GPS} {Systemfor} {Control} of an {Off}-{Road} {Vehicle}},
	url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=3364},
	abstract = {This paper evaluates the ability of an inexpensive dead reckoning system, initialized using carrier phase differential GPS, to provide adequate position and attitude estimation for the control of a farm tractor during short GPS outages. The dead reckoning system allows for continuous control of the vehicle through these GPS outages. An Extended Kalman Filter (EKF) combines the dead reckoning system and cm-level Carrier- Phase Differential GPS (DGPS) measurements for continuous position and attitude estimation of an off-road vehicle. The cm-level accuracy of the DGPS allows for precise calibrations of the plant and sensor models in order to improve the accuracy of the dead reckoning system. Furthermore, it may be possible to reacquire carrier-phase integers more rapidly after short GPS outages, through the continuous position estimation of the dead reckoning system. Analysis based on the short-term integration of sensor noise is used to determine bounds on the position accuracy over time. Results are given which verify the ability of the dead reckoning system’s position and attitude estimation for control of a farm tractor through a short GPS outage.},
	language = {en},
	urldate = {2024-06-20},
	author = {Bevly, David M. and Rekow, Andrew and Parkinson, Bradford},
	month = sep,
	year = {1999},
	pages = {2061--2070},
}

This paper evaluates the ability of an inexpensive dead reckoning system, initialized using carrier phase differential GPS, to provide adequate position and attitude estimation for the control of a farm tractor during short GPS outages. The dead reckoning system allows for continuous control of the vehicle through these GPS outages. An Extended Kalman Filter (EKF) combines the dead reckoning system and cm-level Carrier- Phase Differential GPS (DGPS) measurements for continuous position and attitude estimation of an off-road vehicle. The cm-level accuracy of the DGPS allows for precise calibrations of the plant and sensor models in order to improve the accuracy of the dead reckoning system. Furthermore, it may be possible to reacquire carrier-phase integers more rapidly after short GPS outages, through the continuous position estimation of the dead reckoning system. Analysis based on the short-term integration of sensor noise is used to determine bounds on the position accuracy over time. Results are given which verify the ability of the dead reckoning system’s position and attitude estimation for control of a farm tractor through a short GPS outage.