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Satellite and Terrestrial Radio Positioning Techniques: A signal processing perspective

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* The first book to combine satellite and terrestrial positioning techniques - vital for the understanding and development of new technologies

* Written and edited by leading experts in the field, with contributors belonging to the European Commission's FP7 Network of Excellence NEWCOM++ Applications to a wide range of fields, including sensor networks, emergency services, military use, location-based billing, location-based advertising, intelligent transportation, and leisure

Location-aware personal devices and location-based services have become ever more prominent in the past few years, thanks to the significant advances in position location technology. Sensor networks, geographic information, emergency services, location management, location-based billing, location-based advertising, intelligent transportation, and leisure applications are just some of the potential applications that can be enabled by these techniques.

Increasingly, satellite and terrestrial positioning techniques are being combined for maximum performance; to produce the next wave of location-based devices and services, engineers need to combine both components. This book is the first to present a holistic view, covering all aspects of positioning: both terrestrial and satellite, both theory and practice, both performance bounds and signal processing techniques. It will provide a valuable resource for product developers and R&D engineers, allowing them to improve existing location techniques and develop future approaches for new systems.

  • Combines satellite and terrestrial positioning techniques, using a signal processing approach.
  • Discusses the applicability of developed techniques to emerging standards, such as LTE Advanced or WiMAX II, through the issue of ranging measurement with multicarrier signals.
  • Contains quantitative performance results for ranging, positioning, and tracking for various systems.

Author(s): Davide Dardari, Marco Luise, Emanuela Falletti
Edition: 1
Publisher: Academic Press
Year: 2011

Language: English
Pages: 446
Tags: Информатика и вычислительная техника;Обработка медиа-данных;Обработка изображений;

Satellite and Terrestrial Radio Positioning Techniques: A Signal Processing Perspective......Page 2
Copyright......Page 3
Preface......Page 4
Foreword......Page 5
Acknowledgements......Page 9
Acronyms and Abbreviations......Page 10
1.1.1 Context and Applications......Page 20
1.1.2 Classification of Wireless Positioning Systems......Page 21
1.1.2.1 Classification Based on Available Measurements......Page 22
Received Signal Strength (RSS) Measurements......Page 23
Connectivity......Page 24
1.1.2.2 Classification Based on Network Configuration......Page 25
1.1.3 Performance Metrics......Page 27
1.2 Positioning and Navigation Systems......Page 28
1.2.1 Satellite-Based Systems......Page 29
1.2.2 Augmentation Systems and Assisted GNSS......Page 31
1.2.3 Terrestrial Network-Based Systems......Page 32
1.2.3.2 Positioning in Wireless Local Area Networks (WLANs)......Page 33
1.2.3.4 Positioning in WSNs......Page 34
1.2.3.5 The Ultra-Wide Band (UWB) Technology......Page 35
1.3 Application of Signal Processing Techniques to Positioning and Navigation Problems......Page 36
1.3.1.2 Maximum Likelihood Estimator......Page 37
1.3.4.1 Bayesian Filtering......Page 38
References......Page 40
2.1.1 Global Positioning System (GPS)......Page 43
2.1.1.1 GPS L1......Page 46
2.1.1.2 GPS L2......Page 47
2.1.1.3 GPS L5 and Modernized GPS......Page 48
2.1.2 Galileo......Page 50
2.1.2.1 Galileo E1......Page 52
2.1.2.2 Galileo E6......Page 54
2.1.2.3 Galileo E5......Page 56
2.1.3 GLONASS......Page 58
2.1.3.2 GLONASS Navigation Signals......Page 60
2.1.4 Compass/BeiDou and Regional GNSSs......Page 63
2.2 GNSS Receivers......Page 64
2.2.1 Overall Architecture......Page 65
2.2.2 Signal Acquisition......Page 67
2.2.3 Signal Tracking......Page 70
2.2.3.1 Carrier-Tracking Loops: the PLL and the FLL......Page 72
2.2.3.2 Code Delay Tracking: the DLL......Page 73
2.2.4 Navigation Processing......Page 75
2.2.4.1 GPS Time Scale......Page 76
2.2.4.2 Absolute or Relative Pseudorange Measurements......Page 77
2.2.5 Pseudorange Error Sources......Page 78
2.3 Augmentation Systems and Assisted GNSS......Page 80
2.3.1 Differential GPS......Page 81
2.3.2 Satellite-Based Augmentation Systems......Page 83
2.3.5 Assisted GNSS......Page 84
2.3.5.1 The Assistance Message......Page 87
2.3.5.2 Assisted GNSS Standards in LTE Networks......Page 89
References......Page 90
3.1 Fundamentals on Positioning and Navigation Techniques in Terrestrial Networks......Page 93
3.1.1.1 Received Signal Strength Methods......Page 94
3.1.1.2 Time-of-Arrival Methods......Page 95
3.1.1.4 Angle-of-Arrival Methods......Page 97
Deterministic Techniques......Page 99
Statistical Techniques......Page 103
3.1.2.2 Mapping (Fingerprinting) Techniques......Page 107
3.1.3 Error Sources in Localization......Page 108
ML TOA Estimation in the Presence of Multipath......Page 110
3.1.3.2 Clock Drift......Page 112
Clock Drift in Two-Way Ranging Protocols......Page 113
NLOS Condition Detection......Page 115
NLOS Mitigation Methods......Page 117
3.2 Positioning in Cellular Networks......Page 118
3.2.1.2 Fingerprinting Techniques in Cellular Networks......Page 119
3.2.1.3 Positioning in Cellular Networks in the Presence of Propagation Errors......Page 121
3.3 Positioning in Wireless LANs......Page 123
3.3.1 Architecture of a WLAN......Page 124
3.3.2 IEEE 802.11a/b/g Standards......Page 125
3.3.3.1 Position-Related Signal Parameters......Page 126
Time of Arrival (TOA)......Page 128
Time Difference of Arrival (TDOA)......Page 130
Mapping Techniques......Page 131
3.4.1.1 The IEEE 802.15.4 ZigBee Physical Layer......Page 132
Interferometry......Page 134
3.4.1.3 The IEEE 802.15.4a UWB Physical Layer......Page 135
3.4.2.1 TOA Estimation Algorithms for UWB Signals......Page 137
Peak Detection-Based Estimators......Page 139
Thresholding-Based Estimator......Page 140
3.4.2.2 Energy Detection-Based TOA Estimation......Page 142
First Path Detection......Page 144
3.4.3 Positioning Approaches for WSNs......Page 148
Weighted Least-Squares......Page 149
Projections onto Convex Sets......Page 150
3.4.3.1 Multihop Position Estimation......Page 152
Incremental Algorithms......Page 153
3.4.3.2 Range-Free Positioning......Page 155
3.4.3.3 Anchor-Free Positioning......Page 156
The Robust Quad Algorithm......Page 157
References......Page 162
4.1 Accuracy Bounds in Parameter Estimation and Positioning......Page 172
4.1.1 Fundamental Limits in TOA Ranging with UWB Signals......Page 173
The Cramér–Rao Lower Bound (CRB)......Page 174
The Ziv–Zakai Lower Bound (ZZB)......Page 175
4.2 Variations on the Cramér–Rao Bounds......Page 178
4.2.1 Cramér–Rao Bounds on TOA Estimation in the UWB Multipath Channel......Page 179
4.2.2 CRBs for UWB Multipath Channel Estimation: Impact of the Overlapping Pulses......Page 181
Statistical Channel Model......Page 182
4.2.2.2 Computation of the Bounds......Page 185
4.3.1 Signal and Channel Models for UWB Scenarios......Page 188
4.3.2 Derivation of the Ziv–Zakai Lower Bound......Page 190
4.3.3 Numerical Results in the Presence of Multipath......Page 192
4.4.1 Theoretical Bounds for Direct Position Estimation in GNSS......Page 194
4.4.1.1 Direct Position Estimation......Page 198
4.4.1.2 CRBs for the Conventional Approach......Page 199
4.4.1.3 CRB for the DPE Approach......Page 202
4.4.1.4 Numerical Results......Page 205
4.4.2 Theoretical Performance Limits in Cooperative Localization......Page 209
4.4.2.1 Signal Model......Page 210
4.4.2.2 Analysis of the CRB......Page 211
4.4.3 Bounds for TOA Estimation in the Presence of Interference......Page 213
Disjoint Spectra......Page 217
Slowly-Varying S(f)......Page 218
References......Page 219
5.1 Advanced UWB Positioning Techniques......Page 223
5.1.1 TOA Estimators Operating in the Frequency Domain......Page 224
5.1.1.1 MLE of the Instantaneous Phase......Page 227
5.1.1.2 Instantaneous ML and Phase-Slope-Based TOA Estimators......Page 230
5.1.1.3 Optimal ML-Based and Phase-Slope-Based TOA Estimators......Page 231
5.1.2 Joint Range and Direction of Arrival Estimation......Page 233
Coarse TOA Estimation......Page 237
Fine TOA Estimation......Page 239
Numerical Results......Page 240
5.1.3 TOA Estimation in the Presence of Interference......Page 243
5.1.4.1 Frequency-Domain High-Resolution TOA Estimation......Page 246
Minimum Variance (MV) and Normalized Minimum Variance (NMV) Criteria......Page 247
5.1.4.2 Characterization of the Range Bias......Page 248
Deterministic Model for the Bias: The Wall Extra Delay (WED) Model......Page 249
5.2 MIMO Positioning Systems......Page 250
5.2.1 CRB for the Joint Estimation of TOA and AOA in MIMO Systems......Page 251
5.2.2 A Practical Range Estimator for SIMO Systems......Page 254
5.3 Advanced Geometric Localization Approaches......Page 257
5.3.1 Bounded-Error Distributed Estimation......Page 258
5.3.1.1 Robust Centralized Approach......Page 259
5.3.1.2 Idealized Robust Distributed Approach......Page 260
5.3.1.3 Implementation Issues and Results......Page 261
5.3.2 Projections onto Convex Sets (POCS) Algorithms......Page 264
5.4 Cooperative Positioning......Page 277
5.4.1 Introduction to Cooperative Localization......Page 278
5.4.2 Cooperative LS......Page 280
5.4.3 Cooperative POCS......Page 284
Simulation Results......Page 287
5.4.4 Positioning Using Active and Passive Anchors......Page 290
5.4.5 Distributed Positioning Based on Belief Propagation......Page 296
5.4.5.1 Network Model......Page 298
5.4.5.2 A Distributed BP-Based Positioning Algorithm......Page 299
5.4.5.3 BP-Based Cooperative Positioning Using Particle Filters......Page 301
Fundamental Performance Limits for Stochastic Networks......Page 303
Performance Analysis......Page 304
5.5 Cognitive Positioning for Cognitive Radio Terminals......Page 307
5.5.1 Cognitive TOA Estimation......Page 308
5.5.2 Filter-Bank Multicarrier Ranging Signals......Page 312
5.5.3 Cognitive Bounds and Algorithms with Multicarrier Signals......Page 315
5.5.3.1 Bounds for CP in the ACGN Channel......Page 317
5.5.3.2 Optimum Signal Design for Cognitive Positioning in the ACGN Channel......Page 318
5.5.3.3 Algorithms for Cognitive Positioning......Page 319
Simulation Results......Page 322
Concluding Remarks......Page 323
References......Page 324
6 Signal Processing for Hybridization......Page 332
6.1.1 Bayesian Belief......Page 333
6.1.2 Dynamic Models......Page 335
6.1.3 Generic Structure of a Bayesian Filter......Page 337
6.1.4.1 Basic Examples of EKF Models to Solve the Localization Problem......Page 339
Example 1: Observation Model for UWB-Distance Measurements......Page 341
Example 2: Observation Model for ZigBee-RSS Measurements......Page 342
Example 3: Hybrid Observation Model for UWB-Distance and ZigBee-RSS Measurements......Page 343
6.1.4.2 A More Complex Example: Extended Kalman Filter with Trackingof the NLOS Bias......Page 344
6.1.4.3 Adaptive EKF......Page 345
Experimental Results......Page 346
6.1.4.4 Advanced KF Architectures......Page 347
6.1.5 Particle Filters......Page 348
6.1.5.1 Sequential Importance Resampling......Page 350
6.1.5.2 Auxiliary Particle Filter......Page 351
6.1.5.3 Cost-Reference Particle Filtering......Page 353
6.2 Hybrid Terrestrial Localization Based on TOA + TDOA + AOA Measurements......Page 355
6.3 Hybrid Localization Based on GNSS and Inertial Systems......Page 359
6.3.1 Inertial Measurement Units and Inertial Navigation......Page 360
6.3.1.1 Principles of Strapdown Mechanization......Page 362
6.3.2 Classic Integration of a GNSS Receiver with Inertial Sensors......Page 363
6.3.2.1 Loose Integration......Page 365
6.3.2.2 Tight Integration......Page 366
6.3.3.1 Measurement Equation......Page 368
6.3.3.2 State Equation......Page 371
6.3.3.3 Conceptual DPE Solution and Algorithms......Page 372
Square-Root Derivative-Free Kalman Filters......Page 373
Computational Complexity of the Algorithms for DPE......Page 375
6.3.3.4 Performance Comparison of Simulation Results......Page 377
6.3.3.5 Multiple Quadrature Kalman Filtering......Page 378
Multiple SQKF Algorithm......Page 379
Simulated Performance......Page 383
6.4 Hybrid Localization Based on GNSS and Peer-to-Peer Terrestrial Signaling......Page 384
Notations......Page 385
The hdwMDS Cost Function......Page 386
Minimization of the hdwMDS Cost Function......Page 387
Algorithm......Page 389
Simulation Results......Page 390
References......Page 393
7 Casting Signal Processing to Real-World Data......Page 398
7.1.1 Hardware Setup......Page 399
7.1.2.1 Static Scenario......Page 402
7.1.2.2 Dynamic Scenario......Page 404
7.2.1 Hybridization of Radio Measurements with Inertial Acceleration Corrections......Page 405
7.2.2 EKF and SIR-PF for Hybrid Terrestrial Navigation......Page 407
7.2.2.1 Performance of the SIR Particle Filter......Page 408
7.2.2.2 Performance of the EKF......Page 411
7.2.3.1 Setup of the Observation Noise Covariance......Page 412
7.2.3.2 Tracking Algorithms......Page 413
7.2.4 Experimental Results on LOS versus NLOS Propagation Condition Identification......Page 419
7.3 Software-Defined Radio: An Enabling Technology to Develop and Test Advanced Positioning Terminals......Page 422
7.3.1 The Software-Defined Radio Concept......Page 423
7.3.2 SDR Technology in Localization......Page 425
7.3.2.1 Two Examples of SDR Architecture for a GNSS Receiver......Page 426
Software Receiver......Page 427
7.3.2.2 Exploiting SDR to Realize an Advanced Laboratory Prototype......Page 429
References......Page 433
B......Page 435
C......Page 436
F......Page 437
G......Page 438
J......Page 439
M......Page 440
P......Page 441
R......Page 442
S......Page 443
T......Page 444
W......Page 445
Z......Page 446