GNSS for Vehicle Control

GNSS for Vehicle Control

by David M. Bevly, Stewart Cobb

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Overview

As global navigation satellite systems (GNSS) such as GPS have grown more pervasive, the use of GNSS to automatically control ground vehicles has drawn increasing interest. This cutting-edge resource offers professionals a thorough understanding of this emerging application area of GNSS. Written by highly regarded authorities in the field, this unique reference covers a wide range of key topics, including ground vehicle models, pseudolites, highway vehicle control, unmanned ground vehicles, farm tractors, and construction equipment. This book is supported with over 150 illustrations and more than 180 equations.

Contents Overview:

GNSS and Other Navigation Sensors

Vision Aided Navigation Systems

Vehicle Modeling

Navigation Systems

Vehicle Dynamic Estimation Using GPS

GNSS Control of Ground Vehicles

Pseudolites for Vehicle Navigation

Estimation Methods

Product Details

ISBN-13: 9781596933019
Publisher: Artech House, Incorporated
Publication date: 08/31/2010
Pages: 247
Sales rank: 914,198
Product dimensions: 6.20(w) x 9.10(h) x 0.80(d)

About the Author

David Bevly is an associate professor in Department of Mechanical Engineering at Auburn University, where he directs the GPS and Vehicle Dynamics Laboratory (GAVLAB). He is a member of the American Society of Mechanical Engineers and the Institute of Navigation. He holds an M.S. and Ph.D. in mechanical engineering from MIT and Stanford University, respectively. Stewart Cobb is a founder of Novariant Corporation, where he designs GPS receivers and pseudolites for precise control of air and ground vehicles. He holds an M.S. and Ph.D. in aeronautics and astronautics from MIT and Stanford University, respectively. He also holds an M.S. in systems management for the University of Southern California.

Table of Contents

Preface xiii

Acknowledgments xvii

1 GNSS and Other Navigation Sensors 1

1.1 Global Navigation Satellite System (GNSS) 1

1.1.1 Description of a Typical GNSS 2

1.1.2 Simple (Pseudorange) GNSS Navigation 3

1.1.3 Differential GNSS Navigation 6

1.1.4 Precise (RTK) GNSS Navigation 8

1.1.5 Current and Future GNSS Constellations 11

1.2 Pseudolites 14

1.2.1 Pseudolite Basics 14

1.2.2 Pseudolite/GNSS Navigation 14

1.2.3 Differential Pseudolite/GNSS Navigation 15

1.2.4 Pseudolite Self-Synchronization 16

1.2.5 Stand-Alone Pseudolite Navigation 16

1.2.6 Conflicts with GNSS Frequencies 17

1.3 Inertial Navigation Systems (INS) 18

1.3.1 Linear Inertial Instruments: Accelerometers 18

1.3.2 Angular Inertial Instruments: Gyroscopes 20

1.3.3 Ideal Inertial Navigation 21

1.3.4 Sensing Earth Effects 23

1.3.5 Inertial Instrument Errors 25

1.3.6 Inertial Error Propagation 30

1.4 Odometer Technology 31

1.4.1 Quantization 32

1.4.2 Wheel Slip 32

1.4.3 Wheel Radius Error 33

1.5 GNSS/Inertial Integration 34

References 35

2 Vision Aided Navigation Systems 39

2.1 Lane Positioning Methods 40

2.1.1 Lidar-Based Positioning 40

2.1.2 Camera-Based Positioning 42

2.2 Coordinate Frame Rotation and Translation 43

2.2.1 Two-Dimensional Rotations 44

2.2.2 Three-Dimensional Rotations 45

2.2.3 Coordinate Frame Translation 46

2.2.4 Global Coordinate Frame Rotations 47

2.3 Waypoint-Based Maps 48

2.4 Aiding Position, Speed, and Heading Navigation Filter with Vision Measurements 49

2.4.1 Two-Dimensional Map Construction 50

2.4.2 Measurement Structure 51

2.4.3 Checking Waypoint Map Position 51

2.4.4 Results 52

2.5 Aiding Closely Coupled Navigation Filter with Vision Measurements 52

2.5.1 Three-Dimensional Map Construction 54

2.5.2 Measurement Structure 56

2.5.3 Checking Waypoint Map Position 58

2.5.4 Results 58

References 59

3 Vehicle Modeling 61

3.1 Introduction 61

3.2 SAE Vehicle Coordinates 61

3.3 Bicycle Model 63

3.3.1 Basics 63

3.3.2 Understeer Gradient 70

3.3.3 Four-Wheel Bicycle Model 71

3.4 Tires 74

3.4.1 Basics 74

3.4.2 Contact Patch and Slip 74

3.4.3 Tire Models 76

3.5 Roll Model 79

3.5.1 Free Body Diagram 79

3.5.2 Equation of Motion 80

3.5.3 State Space Representation 80

3.6 Additional Models Used in this Work 80

3.6.1 Two-Wheeled Vehicle 81

3.6.2 Trailer Model 82

3.7 Vehicle Model Validation 84

References 88

4 Navigation Systems 91

4.1 Introduction 91

4.2 Kalman Filter 92

4.3 GPS/INS Integration Architectures 93

4.3.1 Loose Coupling 93

4.3.2 Close Coupling 94

4.4 Speed Estimation 95

4.4.1 Accelerometer and GPS 96

4.4.2 Accelerometer, GPS, and Wheel Speed 102

4.5 Heading Estimation 107

4.6 Position, Speed, and Heading Estimation 111

4.6.1 Coordinate Conversion 112

4.6.2 Accelerometer, Yaw Rate Gyroscope, GPS, and Wheel Speed 113

4.7 Navigation in the Presence of Sideslip 120

4.7.1 Generation of Sideslip 120

4.7.2 Sideslip Compensation with a Dual Antenna GPS Receiver 122

4.8 Closely Coupled Integration 130

References 143

5 Vehicle Dynamic Estimation Using GPS 145

5.1 Introduction 145

5.2 Sideslip Calculation 146

5.3 Vehicle Estimation 147

5.4 Experimental Setup 148

5.4.1 Test Scenarios 148

5.5 Kinematic Estimator (Single GPS Antenna) 149

5.6 Kinematic Kalman Filter (Dual Antenna) 151

5.7 Tire Parameter Identification 154

5.8 Model-Based Kalman Filter 160

5.8.1 Linear Tire Model 161

5.8.2 Nonlinear Tire Model 164

5.8.3 Estimator Accuracies 170

5.9 Conclusions 171

Acknowledgments 172

References 172

6 GNSS Control of Ground Vehicles 175

6.1 Introduction 175

6.2 Vehicle Model 175

6.3 Speed Controller 179

6.4 Vehicle Steering Control 181

6.4.1 Classical Steer Angle Controller 181

6.4.2 Classical Yaw Rate Controller 182

6.5 Waypoint Control 185

6.5.1 Heading Model 185

6.5.2 Heading Error Calculations 186

6.5.3 Heading Control 187

6.5.4 Simulation Results 190

6.6 Lateral Control 192

6.6.1 Error Calculation 193

6.6.2 Lateral Position Model 198

6.6.3 Lateral Position Control 200

6.6.4 Simulation Results 203

6.7 Implement/Trailer Control 203

6.7.1 Trailer Model 204

6.7.2 Error Calculation 206

6.7.3 Trailer Control 208

6.7.4 Simulation Results 210

References 212

7 Pseudolites for Vehicle Navigation 215

7.1 Pseudolite Applications 215

7.1.1 Open-Pit Mining 216

7.1.2 Construction Sites 218

7.1.3 Urban Navigation 218

7.1.4 Indoor Applications 219

7.2 Pseudolite Systems 221

7.2.1 IntegriNautics IN400 221

7.2.2 Novariant Terralite XPS System 223

7.2.3 Locata LocataLites 225

References 226

Appendix Estimation Methods 229

A.1 Introduction 229

A.2 System Model 229

A.3 Discretization 231

A.4 Least Squares 233

A.5 Weighted Least Squares 236

A.6 Recursive Weighted Least Squares 243

A.7 Kalman Filter 246

A.8 Extended Kalman Filter 249

A.9 Initialization 252

References 252

About the Authors 253

Index 257

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