Accueil || Parcours || Recherche || S'enregistrer || Mon Compte || Contacts || Aide || Langues
Kubrak, Damien (2007) Etude de l'hybridation d'un récepteur GPS avec des capteurs bas-coûts pour la navigation personnelle en milieu urbain. Doctorat Electronique et Communications, ENST - COMELEC Communication et Electronique, ENST p.227.
Plein texte disponible en tant que :
|
|
Résumé
First driven by the regulation on emergency calls in the United States (E-911), Location Based Services (LBS) are currently gaining more and more importance in everyday life. Numerous positioning technologies are foreseen to allow the location of one user whether he is indoors or outdoors. Among these techniques, GPS and even more GNSS are well adapted to applications requiring accurate positioning whatever the environment (urban or rural). Such a positioning technique requires no extra infrastructure but a chipset to decode and process GPS signals. As a consequence, this makes it very suitable to fulfil the location requirements of applications such as emergency services (US E911), guidance of rescue teams, in-vehicle navigation, e-tourism… The technique has nevertheless limitations due to errors that affect the incoming signals. Because Location Based Services are likely to be deployed in urban areas, strong multipath may affect the signals, contributing to a high position bias. GPS signals may also be blocked or faded by buildings, which may expose the receiver to cross-correlation distortions in case of large difference between the Signal-to-Noise Ratios (SNRs), decreasing in the same time the accuracy and the availability of the positioning service.
The ability of providing a position solution especially indoors is then a great challenge that can be partially handled with High Sensitivity GPS or Assisted GPS solutions. However, such processing improvements still encounter big issues in the aforementioned harsh environments because of the weak power of the signals to acquire and process. As a consequence, complementary techniques shall be used to support or replace GPS-based positioning systems. Among the possible augmentations, inertial sensor-based techniques are promising ones since they may offer a cost-effective means of improving the overall performance despite the intrinsic low accuracy and stability of the sensors output.
The purpose of this thesis is to investigate the use of such low-cost sensors as a self-contained augmentation of a GPS-based positioning system. More specifically, this study addresses the improvement of the position solution availability and accuracy, as well as the decrease of the processing load of HSGPS/AGPS receivers thanks to information provided by the set of sensors.
In the first place, the performance of the new GPS processing techniques (HSGPS and AGPS) is analysed based on theoretical simulations and field test trials. Results from these test campaigns show that a good accuracy is achievable in urban areas, even if multipath and cross-correlations degrade the overall performance. AGPS is shown to give better measurements than HSGPS, which makes it more suitable for hybridisation purposes. However, there is an unavoidable lack of availability indoors where GPS signals are too weak to be processed.
The augmentation of the aforementioned GPS-based navigation solutions is then addressed through the use of low-cost sensors (typically accelerometers, gyroscopes, magnetometers and a pressure sensor). Different pure inertial navigation algorithms are detailed and optimised mechanisations designed to compensate for the low performance of the low-cost sensors used throughout this thesis are proposed. In particular, an attitude filter capable of dynamically estimating the gyroscope biases is developed and tested in actual conditions.
The improvement of the acquisition stage of AGPS and HSGPS receivers is investigated based on the self-contained augmentations previously described. The reduction of the Doppler uncertainty due to user’s motion is more specifically addressed. Tests on data collected during urban vehicle trials are used to assess the performance of the proposed technique. It is shown that the user’s Doppler contribution can be well estimated whatever the dynamic experienced by the receiver, which contributes to the decrease of the acquisition stage complexity. However it should be pointed out that better performances are obtained in the pedestrian navigation case than in the land vehicle navigation case.
The position solution availability and accuracy in urban canyons and indoor environments is finally addressed through several hybridisation schemes aimed at fusing the different GPS modules (HSGPS or AGPS) and the low-cost inertial sensors. A non-standard tight coupling scheme is proposed in the frame of land vehicle navigation. Results show that urban navigation using only 2 pseudorange and Doppler measurements is possible, even if the accuracy of the integrated navigation system is sensitive to the geometry of the satellite used for hybridisation. A real time loose coupling prototype is implemented and tested for the specific pedestrian navigation case. The accuracy of the integrated navigation system is shown to stay within 10 metres from the reference trajectory even during complete GPS outages of about 2 minutes according to the trials exercised.
| Type d'EPrint: | Thèse (Doctorat) |
|---|---|
| Directeur de Thèse: | Macabiau, Christophe et Boucheret, Marie-Laure |
| Date: | 24 Mai 2007 |
| Jury de Thèse: | Maral, Gérard et Hein, Günter et Lachappelle, Gérard et Monnerat, Michel |
| Ecole Doctorale: | ED 130 INFORMATIQUE, TELECOMMUNICATIONS ET ELECTRONIQUE (EDITE) |
| Discipline: | Electronique et Communications |
| Fonds: | ENST |
| Institution: | ENST |
| Laboratoire: | ENST - COMELEC Communication et Electronique |
| Sujets: | 2. Sciences et technologies de l'information et de la communication |
| Mots-clés libres: | Hsgps, Agps, Ins, Hybridisation, Kalman filter |
| Code ID: | 2803 |
| Déposé par : | Damien Kubrak |
| Déposé le : | 28 Septembre 2007 |
Table des Matières
Table of Contents
REMERCIEMENTS I
RESUME III
ABSTRACT VII
TABLE OF CONTENTS IX
LIST OF FIGURES XIII
LIST OF TABLES XIX
ABBREVIATIONS XXI
CHAPTER 1: INTRODUCTION 1
1.1 BACKGROUND 1
1.2 MOTIVATIONS AND OBJECTIVES 2
1.3 CONTRIBUTIONS 3
1.4 THESIS OUTLINE 5
CHAPTER 2: GPS-BASED POSITIONING 7
2.1 THE GLOBAL POSITIONING SYSTEM 8
2.1.1 Fundamentals 8
2.1.1.1 Space Segment 8
2.1.1.2 Control Segment 10
2.1.1.3 User Segment 11
2.1.2 GPS Signal Processing 12
2.1.2.1 GPS Signal Acquisition 13
2.1.2.2 GPS Signal Tracking 17
2.1.3 GPS Measurements 22
2.1.3.1 Pseudorange Measurement 22
2.1.3.2 Doppler Measurement 23
2.1.3.3 Carrier Phase Measurement 24
2.1.4 Measurement Errors 24
2.1.4.1 Satellite Orbital Error ΔD 24
2.1.4.2 Ionospheric Error ΔI 24
2.1.4.3 Tropospheric Error ΔT 25
2.1.4.4 Multipath μ 25
2.1.4.5 Time Synchronisation Δb 25
2.1.4.6 Tracking Loops Jitter 25
2.2 GPS PROCESSING ENHANCEMENT 26
2.2.1 Positioning Technologies and Issues 26
2.2.2 High Sensitivity GPS 27
2.2.2.1 Principle 27
2.2.2.2 Performance Overview 29
2.2.3 Assisted GPS 30
2.2.3.1 Principle 30
2.2.3.2 Enhanced AGPS 32
2.2.3.3 Acquisition Performance 33
2.3 HS-GPS / AGPS PERFORMANCE ANALYSIS 35
2.3.1 HSGPS / AGPS Modules 35
2.3.2 Performance Assessment 36
2.3.2.1 Accuracy 36
2.3.2.2 Time-To-First-Fix 37
2.3.2.3 Availability 37
2.3.3 Comparative Test Results 37
2.3.3.1 Light Indoor Environment 37
2.3.3.2 Urban Street Environment 39
2.3.3.3 Kinematic Urban Test 40
2.3.3.4 Indoor Test 41
2.4 CONCLUSION 41
CHAPTER 3: INERTIAL NAVIGATION SYSTEMS 44
3.1 INERTIAL NAVIGATION OVERVIEW 45
3.1.1 Basic principle 45
3.1.2 Frames and Coordinates 45
3.1.3 Sensors 46
3.1.3.1 Accelerometer 46
3.1.3.2 Gyroscope 47
3.1.3.3 Measurements Errors 48
3.2 STRAP DOWN ATTITUDE COMPUTATION 48
3.2.1 Attitude Algorithm 49
3.2.2 Attitude Initialisation 51
3.2.3 Euler’s Angles Singularity Issue 52
3.3 MEMS SENSOR UNIT PERFORMANCE OVERVIEW 54
3.3.1 Xsens Motion Tracker 54
3.3.1.1 Accelerometer 54
3.3.1.2 Gyroscopes 55
3.3.2 Gyroscope Output Approximation 56
3.4 CLASSICAL INERTIAL NAVIGATION SYSTEM 58
3.4.1 Fundamental Inertial Differential Equation 58
3.4.2 INS Mechanisation in the Navigation Frame 60
3.4.3 Expected Accuracy 61
3.5 THE PARTICULAR CASE OF THE PEDESTRIAN NAVIGATION 62
3.5.1 Mechanisation in the Navigation Frame 63
3.5.2 Travelled Distance Estimation 65
3.5.2.1 Parameters 65
3.5.2.2 Velocity Models 68
3.5.2.3 Regression Coefficients 69
3.5.3 Displacement Direction Estimation 73
3.5.4 Unconstrained Navigation Issue 74
3.5.5 PNS Mechanisation 76
3.5.6 Expected Accuracy 76
3.6 CONCLUSION 79
CHAPTER 4: SENSOR-BASED AUGMENTATIONS 80
4.1 PRESSURE SENSOR 81
4.1.1 Principle and Output Model 81
4.1.2 Performance assessment 82
4.1.3 Improvement of the Position Solution 83
4.2 MAGNETIC FIELD SENSOR 85
4.2.1 Earth Magnetic Field 85
4.2.2 Sensor Output Model 86
4.2.3 Magnetic Heading 86
4.2.4 Calibration Procedures and Magnetic Interferences 87
4.3 DRIFT-FREE ATTITUDE FILTER 89
4.3.1 Inclination Filter 90
4.3.1.1 State Transition Models 90
4.3.1.2 Measurement Models 94
4.3.1.3 Inclination Filter Summary 95
4.3.2 Heading Filter 95
4.3.2.1 State Transition Models 95
4.3.2.2 Measurements Models 97
4.3.2.3 Heading Filer Summary 98
4.3.3 Optimised Drift-Free Attitude Filter 99
4.3.4 Drift-Free Attitude Filter 100
4.3.4.1 Design n°1: Attitude Filter using all the Sensors 100
4.3.4.2 Design n°2: Attitude Filter using only 1 Gyroscope 100
4.3.5 Test Results 101
4.3.5.1 The Pedestrian Navigation Case 102
4.3.5.2 The Land Vehicle Navigation 106
4.4 OTHER AUGMENTATION TECHNIQUES 109
4.4.1 Zero velocity UPdaTe (ZUPT) 109
4.4.2 Velocity and Height Constraints 110
4.5 CONCLUSION 110
CHAPTER 5: SENSORS AIDING FOR GPS ACQUISITION 112
5.1 INTRODUCTION 113
5.2 RECEIVER DOPPLER UNCERTAINTY 115
5.2.1 Satellite Contribution 115
5.2.2 Local Oscillator Contribution 118
5.2.3 User Contribution 119
5.3 SENSORS AIDING FOR DOPPLER UNCERTAINTY REDUCTION 120
5.3.1 Motion Recognition 120
5.3.2 Sensor Fusion & Integration Scheme 121
5.3.3 Satellite Geometry Issue 123
5.3.4 On-Demand Doppler Estimation 125
5.3.5 Doppler Reduction Procedure 126
5.4 TEST RESULTS 127
5.4.1 The Pedestrian Navigation Case 127
5.4.2 The Land Vehicle Navigation Case 129
5.5 CONCLUSIONS 131
CHAPTER 6: GPS/IMU HYBRIDISATION FOR PERSONAL NAVIGATION 134
6.1 INTEGRATION STRATEGIES & ARCHITECTURES 135
6.1.1 Loose Coupling 135
6.1.2 Tight Coupling 136
6.1.3 Sensors Augmentation 137
6.1.4 Practical Use Cases 138
6.2 LAND VEHICLE NAVIGATION CASE 138
6.2.1 Introduction 138
6.2.2 Integrated Navigation System 140
6.2.2.1 INS Mechanisation 140
6.2.2.2 Measurement Equations 143
6.2.2.3 Coupling Methodology 144
6.2.3 Test Results 148
6.2.4 Conclusion 156
6.3 PEDESTRIAN NAVIGATION CASE 157
6.3.1 Introduction 157
6.3.2 PNS Mechanisation Performance 158
6.3.2.1 Static Performance 158
6.3.2.2 Constrained Navigation 159
6.3.2.3 Unconstrained Navigation 162
6.3.2.4 Conclusion 163
6.3.3 Integrated Navigation System 164
6.3.3.1 Introduction 164
6.3.3.2 Coupling Methodology 165
6.3.3.3 Test Results 171
6.3.4 Conclusion 176
6.4 CONCLUSION 177
CHAPTER 7: CONCLUSIONS AND FUTURE WORK 178
7.1 CONCLUSIONS 178
7.2 FUTURE WORK 180
APPENDIX A: DOPPLER EFFECT 182
APPENDIX B: QUATERNION-BASED ATTITUDE COMPUTATION 186
APPENDIX C: LEAST SQUARES AND KALMAN FILTERING 190
APPENDIX D: FREQUENCY ESTIMATION TECHNIQUES 194
BIBLIOGRAPHY 200
Administrateurs de l'archive uniquement : éditer cet enregistrement