Handbook of position location : theory, practice, and advances

HANDBOOK OF POSITION LOCATION......Page 3
Contents......Page 9
Preface......Page 15
Contributors......Page 25
About the Companion Website......Page 27
PART I Fundamentals of Position Location......Page 29
1.1 Introduction......Page 31
1.2 Basic Methods Used in Positioning Systems......Page 33
1.3.1 GPS......Page 38
1.3.2 Assisted Global Positioning System (A-GPS or Assisted GPS)......Page 40
1.3.3 INS......Page 41
1.3.4 Integrated INS and GPS......Page 42
1.3.6 WLPS......Page 43
1.3.7 Traffic Alert and Collision Avoidance System (TCAS)......Page 44
1.4 Comparison of Basic Methods and Positioning Systems......Page 46
1.5 Summary and Future Applications......Page 47
References......Page 50
2.1 Introduction......Page 53
2.2.1 Error Probability......Page 55
2.2.2 Cramer–Rao Bound......Page 64
2.3.1 GPS......Page 68
2.3.2 INS......Page 72
2.3.3 Camera......Page 73
2.3.4 Network Localization......Page 76
2.3.5 Range Detection Sensors......Page 77
2.5 Practical Error Evaluation Method and Correction......Page 79
2.6 Summary......Page 82
References......Page 83
Chapter 3 Source Localization: Algorithms and Analysis......Page 87
3.1 Introduction......Page 88
3.2.1 TOA......Page 90
3.2.2 TDOA......Page 92
3.2.3 TSOA......Page 93
3.2.4 RSS......Page 95
3.2.5 DOA......Page 96
3.3 Algorithms for Source Localization......Page 97
3.3.1 Nonlinear Methods......Page 98
3.3.2 Linear Methods......Page 108
3.4 Performance Analysis for Localization Algorithms......Page 121
3.4.1 CRLB Computation......Page 122
3.4.2 Mean and Variance Analysis......Page 125
3.5 Conclusion......Page 130
Appendix......Page 131
References......Page 132
4.1 Introduction......Page 135
4.2 Channel Model......Page 137
4.3 Important Statistics for Received Signal Strength (RSS)......Page 139
4.4 Important Statistics for TOA , TDOA, and DOA......Page 143
4.4.1 PDP Statistics and Impact on Localization and Radio Design......Page 144
4.4.2 PSP Statistics and Impact on Localization and Radio Design......Page 151
4.4.3 PAP Statistics and Impact on Localization and Radio Design......Page 155
4.5 Summary of Different Channel Categories......Page 156
4.6 Statistics of Amplitude, Phase, and TOA......Page 157
4.7.3 Rough Surface Channel Modeling......Page 160
4.7.4 Near-Ground Channel Modeling......Page 161
4.8 Inhomogeneous Media Channel Modeling......Page 164
References......Page 166
5.1 Introduction......Page 171
5.2 The Estimation Problem......Page 173
5.2.1 Estimation Problem Classifications......Page 174
5.4 Discrete Kalman Filter......Page 175
5.4.1 Kalman Filter Derivation......Page 176
5.4.2 Kalman Filter Implementation and Practical Considerations......Page 178
5.5 Continuous-Time Kalman Filter......Page 182
5.6 EKF......Page 184
5.7 UKF......Page 194
5.8 CKF......Page 198
5.8.1 Model Reduction Method......Page 199
5.8.3 Projection Method......Page 200
5.9 Measurement Fusion Kalman Filter......Page 204
5.10 Gain-Scheduled Kalman Filter......Page 211
5.11 EnKF......Page 216
5.13 Further Readings......Page 220
References......Page 221
PART II TOA and DOA Based Positioning......Page 225
6.1 Introduction......Page 227
6.2 TDOA Positioning......Page 228
6.2.1 Geometric Interpretation......Page 229
6.3 TOA Positioning......Page 232
6.3.1 Geometric Interpretation......Page 233
6.4 TDOA versus TOA......Page 235
6.5 TOA versus TDOA in the Presence of Noise......Page 236
6.6.1 Taylor Series Approximation......Page 239
6.6.2 Differencing......Page 241
6.7 Pseudorange......Page 248
6.8.1 Impact of NLOS Bias Errors......Page 251
6.8.2 Discarding NLOS Range Estimates......Page 252
6.8.3 NLOS Identification......Page 254
6.8.4 NLOS Mitigation......Page 257
6.9.1 LOS Range Estimates......Page 258
6.9.2 NLOS Range Estimates......Page 259
6.9.3 Combining the LOS and NLOS Range Information......Page 260
References......Page 263
7.1 Introduction......Page 265
7.2 TOA Estimation Methods......Page 268
7.2.1 Conventional Correlation-Based Techniques......Page 272
7.2.2 Deconvolution Methods......Page 274
7.2.3 ML-Based Methods......Page 277
7.2.4 Subspace-Based Techniques......Page 278
7.2.5 BSS-Based Algorithms......Page 281
7.3 Comparison of TOA Estimation Techniques......Page 285
7.4.1 Single-Band Range Estimation Architecture......Page 287
7.4.2 Multiband Range Estimation: General Architecture......Page 288
7.4.3 Noncontiguous Multiband Scenario......Page 290
References......Page 292
8.1.1 Regularization......Page 297
8.1.2 Transmission Approaches......Page 298
8.1.3 Standards......Page 299
8.1.4 UWB Channels......Page 300
8.2.1 Fingerprinting Localization......Page 302
8.2.2 Geometric Localization......Page 304
8.2.3 NLOS Issues......Page 306
8.3.1 System Model......Page 307
8.3.2 ML TOA Estimation......Page 309
8.3.3 Energy Detection-Based TOA Estimation......Page 310
8.3.4 TDT......Page 312
8.3.5 Discussions on IR-Based TOA Estimation......Page 314
8.4 TOA Estimation for MB-OFDM UWB......Page 315
8.4.1 System Model......Page 317
8.4.2 Correlation-Based TOA Estimator......Page 318
8.4.3 Energy Detection-Based TOA Estimator......Page 319
8.4.4 TOA Estimation by Suppressing Energy Leakage......Page 321
8.4.5 Discussions on MB-OFDM-Based TOA Estimation......Page 325
8.5 Conclusions......Page 326
References......Page 327
9.1 Introduction......Page 331
9.2 Antennas and THEIR Parameters......Page 332
9.2.1 Antenna HPBW......Page 334
9.2.4 Antenna Impedance......Page 335
9.2.5 Antenna Return Loss......Page 336
9.2.7 Antenna Gain......Page 337
9.3 Antenna Arrays......Page 339
9.3.1 Smart Antennas......Page 340
9.3.2 Important Parameters of Antenna Arrays......Page 341
9.4 DOA Estimation Methods......Page 345
9.4.1 DAS......Page 349
9.4.2 MUSIC and Root MUSIC......Page 351
9.4.3 DAS and Root MUSIC Fusion......Page 358
9.4.4 Comparison......Page 361
9.5 DOA Estimation for Periodic Sense Transmission......Page 362
Acknowledgments......Page 367
References......Page 368
10.1 Introduction......Page 371
10.2 Impact of Waveform Dispersion on TOA Estimation......Page 373
10.3.1 Waveform Design......Page 375
10.3.2 High-Resolution TOA Estimation via Bandlimited Signals......Page 377
10.4.1 System Model of Propagated Signal......Page 381
10.4.2 Very High-Resolution TOA Estimation via OFDM Subcarriers......Page 382
10.5.1 Layer Thickness Computation and Straight-Line Range Estimation......Page 386
10.6.1 Underground Layer Detection......Page 389
10.6.2 Nanosensor Node Localization within the Human Body......Page 390
10.7 Conclusion......Page 391
References......Page 392
PART III Received Signal Strength Based Positioning......Page 395
11.1 Introduction and Motivation......Page 397
11.1.2 Problem Statement and Outline......Page 398
11.2.1 Multipath Fading and NLOS Propagation......Page 400
11.3 Techniques Using RSS for Position Location......Page 401
11.3.1 Range-Based Positioning......Page 402
11.3.2 RF Fingerprinting......Page 406
11.3.3 Proximity-Based Positioning......Page 408
11.4 Geometric Interpretations of RSS/DRSS Positioning......Page 410
11.4.1 RSS-Based Lateration......Page 413
11.4.2 DRSS-Based Lateration......Page 415
11.5 Location Estimators......Page 418
11.5.1 Theoretical Limits for Location Estimation......Page 419
11.5.2 ML Estimator......Page 420
11.5.3 Nonlinear LS Estimator......Page 421
11.5.4 Linear LS Estimator......Page 423
11.6.1 Simulation Settings......Page 425
11.6.2 Simulation Results......Page 426
11.7 Conclusion......Page 429
References......Page 430
Chapter 12 On the Performance of Wireless Indoor Localization Using Received Signal Strength......Page 433
12.1 Introduction......Page 434
12.2 RSS-based Localization Algorithms......Page 435
12.2.1 Approach Overview......Page 436
12.2.2 Lateration Methods......Page 437
12.2.3 Classification via Machine Learning......Page 439
12.2.4 Probabilistic Approaches......Page 441
12.2.5 Statistical Supervised Learning Techniques......Page 442
12.2.6 Summary of Localization Algorithms......Page 443
12.3.1 Performance Metrics......Page 445
12.3.2 Performance Investigation Using Real Wireless Networks......Page 446
12.4.1 Real-Time Infrastructure Calibration......Page 451
12.4.2 Effects of Employing Multiple Antennas......Page 452
12.4.3 Robust Statistical Methods......Page 454
12.4.4 Revisiting Linear Regression......Page 455
12.4.5 Exploiting Spatial Correlation......Page 456
12.5 Conclusion and Applications......Page 458
References......Page 460
13.1 Introduction......Page 463
13.2.1 Overview......Page 464
13.2.2 Impact of Anchor Placement......Page 466
13.2.3 Heuristic Search......Page 469
13.2.4 Acute Triangular-Based Deployment......Page 471
13.2.5 Adaptive Beacon Placement......Page 473
13.2.6 Optimal Placement via maxL–minE......Page 474
13.3.2 Joint Clustering Technique......Page 483
13.3.4 Convex Hull Selection......Page 485
13.3.5 Selection from High Density of Anchors......Page 487
References......Page 491
14.1 Introduction......Page 495
14.2 Kernel Methods......Page 497
14.2.2 General Mathematical Formulation......Page 498
14.2.3 LANDMARC Algorithm......Page 502
14.2.4 Gaussian Kernel Localization Algorithm......Page 503
14.2.5 Radial Basis Function-Based Localization Algorithm......Page 506
14.2.6 Linear Signal-Distance Map Localization Algorithm......Page 508
14.3.1 MLE......Page 511
14.3.2 Description of Comparison Example......Page 512
14.4.2 Evaluation Procedure......Page 519
14.4.3 Results......Page 520
14.5 Discussion and Conclusion......Page 522
References......Page 523
15.1 Introduction......Page 525
15.2 RF Fingerprints......Page 527
15.3 CDB......Page 528
15.3.2 Building the CDB......Page 529
15.4 Techniques to Reduce the Search Space......Page 536
15.4.1 CDB Filtering......Page 537
15.4.2 Optimized Search Using GA......Page 539
15.5.1 Distance in N-Dimensional RSS Space......Page 541
15.5.2 Pattern Matching Using Artificial Neural Networks......Page 545
15.5.3 Spearman Rank Correlation Coefficient......Page 547
15.6 Experimental Performance......Page 548
15.6.1 Outdoor 850-MHz GSM Network......Page 549
15.6.2 Indoor Wi-Fi Networks......Page 551
15.7.1 RSS-Based Fingerprinting for Multifloor Indoor Positioning......Page 552
15.8 Conclusion......Page 553
References......Page 555
PART IV LOS/NLOS Localization – Identification – Mitigation......Page 559
Chapter 16 NLOS Identification and Localization......Page 561
16.1 Introduction......Page 562
16.2 NLOS Identification......Page 563
16.2.1 Cooperative Methods......Page 565
16.2.2 Single-Node Methods Based on the Range Statistics......Page 568
16.2.3 Single-Node Methods Based on Channel Characteristics......Page 570
16.2.4 Single-Node Hybrid Approach......Page 579
16.3 NLOS Localization......Page 581
16.3.1 RSSI......Page 582
16.3.2 Bidirectional TOA–DOA Fusion......Page 584
16.3.3 Single BN TOA–DOA Fusion with the Assistant Environment Map......Page 585
16.3.4 Multinode TOA–DOA Fusion......Page 586
16.3.5 Comparison......Page 588
References......Page 590
Chapter 17 NLOS Mitigation Methods for Geolocation......Page 595
17.1 Introduction......Page 596
17.2 Geolocation System Model......Page 597
17.3.1 ML-Based Techniques......Page 598
17.3.2 LS-Based Techniques......Page 600
17.3.3 Constrained Optimization Techniques......Page 602
17.3.4 Robust Estimator Techniques......Page 603
17.4 Application of the Single Moving Sensor Geolocation......Page 604
17.4.1 Range Measurements Profile-Based Trimming......Page 605
17.4.2 Reconstruction of Trimmed TOA Profile......Page 609
17.4.3 Robust Trimming with Nonparametric Noise Density Estimator......Page 610
17.4.4 Performance Analysis......Page 612
References......Page 617
Chapter 18 Mobile Position Estimation Using Received Signal Strength and Time of Arrival in Mixed LOS/NLOS Environments......Page 621
18.1.2 Literature Review......Page 622
18.1.4 Organization......Page 625
18.2.1 Existing Techniques for Mobile Position Estimation......Page 626
18.2.2 Path Loss Model......Page 631
18.3.1 TOA Estimation......Page 632
18.3.4 ML......Page 634
18.4.1 FIM of TOA Estimation......Page 635
18.5 Numerical Examples......Page 636
18.6 Conclusions......Page 645
Appendix......Page 646
References......Page 651
19.1 Introduction......Page 657
19.2.1 General Problem Formulation......Page 658
19.2.3 Example of the Measurement Model......Page 660
19.3.1 The Development of GMF......Page 661
19.4.1 Generic PF......Page 667
19.4.2 ARBPF......Page 668
19.5 Lower Bound of Performance......Page 671
19.6 Numerical Results......Page 674
19.6.1 Performance Comparison with Different Algorithms......Page 675
19.6.2 Comparison with Posterior CRLB......Page 676
19.7 Conclusions......Page 678
References......Page 679
PART V Global Positioning......Page 681
20.1 Introduction......Page 683
20.1.2 Spherical Systems......Page 684
20.1.3 Evolution Programs of GNSS Constellations......Page 686
20.2 Principles of Satellite Navigation......Page 688
20.2.2 Impact of Measurement Errors on User Position......Page 690
20.3 The Impact of Geometry......Page 692
20.3.1 GDOP as a Function of Position and Time......Page 695
20.4 Overview on Reference Systems......Page 699
20.4.2 Conventional Terrestrial Reference System......Page 700
20.4.3 Ellipsoidal Coordinates......Page 701
20.4.5 The Global Datum......Page 702
20.5 Structure of the Signal-In-Space......Page 703
20.5.2 The Binary Offset Carrier Modulation......Page 704
20.5.3 The GNSS Transmitted Signal......Page 708
20.6 Current and Modernized GPS Signals......Page 710
20.6.1 MBOC Signal Baseline......Page 711
20.6.2 TMBOC Modulation......Page 713
20.7 Galileo System and SIS......Page 714
20.7.1 E1 CBOC Modulation......Page 715
20.7.2 AltBOC Modulation and Multiplexing Scheme......Page 719
20.8 Error Sources for the Position Evaluation......Page 723
20.8.1 GNSS Positioning......Page 724
20.9.1 Local Area Differential Corrections......Page 727
20.9.2 Wide Area Differential Corrections......Page 728
20.9.3 AGNSS and Cooperative Navigation......Page 730
20.9.4 Trends in GNSS-Related Augmentation Solutions and Technologies......Page 731
References......Page 732
Chapter 21 Digital Signal Processing for GNSS Receivers......Page 735
21.1 Received Signal......Page 736
21.1.1 The Doppler Effect in the Carrier......Page 737
21.2 The General Receiver Structure......Page 738
21.2.1 Sampling Frequency......Page 739
21.2.2 The Digital IF Signal......Page 741
21.3 Acquisition......Page 746
21.3.1 Detection and Estimation Main Strategy......Page 747
21.3.2 Cross Ambiguity Function......Page 749
21.3.3 Refinement of the Estimation of the SIS Parameters......Page 755
21.3.4 Acquisition Performance......Page 757
21.4.1 FFT in the Time Domain......Page 758
21.4.2 FFT in the Doppler Domain......Page 759
21.5 Methods for SIS detection......Page 762
21.5.1 NP Approach......Page 763
21.5.3 Bayesian Sequential Detection......Page 767
21.6.1 Transient between Signal Acquisition and Tracking......Page 770
21.6.2 Fundamentals of Gradient Theory......Page 771
21.6.3 Application to GNSS Signals......Page 772
21.7 Null Seeker and Tracking Loops......Page 775
21.7.1 DLL......Page 777
21.7.2 Carrier Tracking......Page 780
21.7.3 Models of the Tracking Loops......Page 781
21.7.4 Tracking Loop Performance......Page 782
21.8 Estimation of Pseudoranges......Page 784
Appendix A: The Doppler Effect at Baseband......Page 786
References......Page 787
Chapter 22 Kalman Filter-based Approaches for Positioning: Integrating Global Positioning with Inertial Sensors......Page 791
22.1 Introduction......Page 792
22.2.1 State-Space Models......Page 793
22.2.2 Continuous-Time to Discrete-Time Transformation......Page 796
22.2.3 Recursive Estimation and Initial Conditions......Page 798
22.2.4 The EKF......Page 800
22.2.5 The Unscented KF......Page 803
22.3.1 State-Space Model......Page 806
22.3.2 Linearization of the Measurement Equation......Page 808
22.3.3 Error Covariance Matrices......Page 810
22.4.1 Structure of an IMU......Page 812
22.4.2 The Coriolis Theorem......Page 813
22.4.3 Mechanization Equations......Page 814
22.5 Noise Characterization of an Inertial Unit......Page 817
22.5.1 IMU Deterministic Errors......Page 818
22.5.2 Modelling the IMU Stochastic Noise......Page 820
22.6.1 Calibrating a High-Grade IMU......Page 832
22.6.2 Calibrating a Low-Grade IMU......Page 833
22.6.3 Initial Alignment......Page 836
22.7 General Architecture for the Loose Integration......Page 841
22.7.1 Loose Integration: State-Space Model......Page 842
22.7.2 Loose Integration: State Transition Matrix......Page 845
22.7.3 Loose Integration: Measurement Equation......Page 847
22.8 General Architecture for the Tight Integration......Page 848
22.8.2 Tight Integration: State Transition Matrix......Page 849
22.8.3 Tight Integration: Measurement Equation......Page 850
22.9 Performance Comparison between Loose and Tight Integration......Page 851
22.9.1 Zone #1: Open-Sky Car Parking......Page 852
22.9.2 Zone #2: Dense Urban Area......Page 853
22.10 General Architecture for the Ultra-Tight Integration......Page 855
22.10.1 Ultra-Tight Integration: Centralized Architecture......Page 856
22.10.2 Ultra-Tight Integration: Federated Architecture......Page 857
Appendix A: MATLAB Code......Page 861
References......Page 864
23.1 Introduction......Page 867
23.2 Signal Power, Noise and Correlation Gain......Page 869
23.2.1 The Correlation Gain......Page 870
23.3.1 Coherent Integration Time Extension......Page 874
23.3.2 Noncoherent Integration Time Extension......Page 876
23.4.1 Data Transition......Page 878
23.4.3 Considerations on the Doppler Frequency......Page 883
23.4.4 Clock Errors and Stability......Page 885
23.4.5. Impact of Doppler Rate......Page 886
23.4.6 Other Factors Impacting Receiver Sensitivity......Page 887
23.5.1 Acquisition Stage......Page 888
23.5.3 Tracking Stage......Page 902
23.6.1 Example of Frequency Aiding in Acquisition......Page 905
23.7.3 Encoded Naviagtion Data......Page 907
References......Page 908
PART VI Network Localization......Page 911
24.1 Introduction......Page 913
24.2 Problem Definition......Page 916
24.3.1 CRLB......Page 918
24.3.2 MLE/Weighted LS......Page 921
24.3.3 Numerical Results......Page 927
24.4 An Overview of Suboptimal Algorithms......Page 929
24.4.1 A Taxonomy of Existing Algorithms......Page 932
24.5 Specific Suboptimal Approaches......Page 933
24.5.1 Sequential LS......Page 934
24.5.2 Optimization-Based Approaches......Page 936
24.5.3 MDS......Page 938
24.5.4 Set-Theoretic Approach: Iterative Parallel Projection Method (IPPM)......Page 941
24.6.1 Localization Accuracy......Page 951
24.6.2 Computational Complexity......Page 957
24.7 NLOS Propagation......Page 958
24.7.2 NLOS Mitigation Example......Page 959
24.7.3 Simulation Results......Page 961
24.8 Summary......Page 965
References......Page 966
25.1 Introduction......Page 971
25.2 Polynomial Function Optimization......Page 973
25.2.1 Polynomial Continuation (Homotopy) Methods......Page 974
25.2.2 SOS and SDP Approaches......Page 975
25.3 Noisy Target Localization......Page 977
25.4 Relative Reference Frame Determination......Page 980
25.4.1 Relative Reference Frame Determination with Distance Measurements......Page 981
25.4.2 Relative Reference Frame Determination with Relative Angle Measurements......Page 982
25.4.3 Noisy Relative Reference Frame Determination......Page 984
25.4.4 Algorithmic Comparison with Some Existing Methods......Page 987
25.4.5 Colinear Anchors......Page 989
25.5 An Extension of the SOS Approach......Page 990
References......Page 991
Chapter 26 Belief Propagation Techniques for Cooperative Localization in Wireless Sensor Networks......Page 995
26.1.1 Classification of Cooperative Localization Methods......Page 996
26.1.2 Measurement Techniques......Page 998
26.2 Probabilistic Localization Based on BP......Page 1000
26.2.1 Introduction to Probabilistic Localization......Page 1001
26.2.2 BP......Page 1002
26.2.3 NBP......Page 1005
26.2.4 NBBP......Page 1008
26.3.1 Correctness of BP......Page 1011
26.3.2 GBP-K......Page 1013
26.3.3 NGBP-JT......Page 1014
26.3.4 NBP-ST......Page 1017
26.3.5 URW-NBP......Page 1022
References......Page 1024
27.1 Introduction......Page 1027
27.2 APS Algorithms......Page 1029
27.2.1 DV-Hop Propagation Method......Page 1030
27.2.2 DV-Euclidean and DV-Radial......Page 1032
27.2.3 DV-Position......Page 1033
27.3.1 Trilateration Review......Page 1034
27.3.3 DV-Hop Range Error......Page 1035
27.3.4 CRLB for DV-Hop Positioning......Page 1039
27.3.5 DV-Position Error......Page 1041
27.4 Discussion......Page 1044
27.5 Related Work......Page 1046
Appendices......Page 1047
References......Page 1052
28.1 Introduction......Page 1055
28.2 Problem Setup......Page 1057
28.3 A Rigid Graph Theoretical Framework for Formation Localization......Page 1059
28.4 Four-Bar Linkage Mechanisms......Page 1062
28.5 A Localization Algorithm Based on Four-Bar Linkage Mechanisms......Page 1064
28.6 Localization of Larger Formations......Page 1070
28.7 Localization with Extra Landmarks......Page 1072
28.8 Availability of More Angle Measurements for Three Agents......Page 1073
28.9 Conclusions......Page 1074
References......Page 1075
PART VII Special Topics and Applications......Page 1077
29.1 Introduction......Page 1079
29.2.1 Exteroceptive Sensors......Page 1080
29.2.2 Proprioceptive Sensors......Page 1084
29.3.1 Global Localization......Page 1086
29.3.2 Relative Localization......Page 1087
29.3.3 SLAM......Page 1088
29.4.1 Appearance-Based Method......Page 1089
29.4.2 Feature-Based Methods......Page 1092
29.4.3 Motion Estimation......Page 1099
29.5 Simultaneous Localization and Mapping......Page 1101
29.5.2 Paradigms of SLAM......Page 1102
29.6 Cooperative Estimation, Filtering, and Sensor Fusion......Page 1107
29.7 Localization Systems in Use for Autonomous Driving......Page 1108
29.7.1 Autonomous Driving Competitions......Page 1109
29.8 Future of Localization in Autonomous Driving......Page 1110
References......Page 1111
30.1.1 Basic Navigation Concepts......Page 1117
30.1.2 Estimating Robot’s Pose......Page 1120
30.1.3 Experimental Verification: Grid-Like Pattern......Page 1122
30.2.1 Problem with RFID-Based Localization......Page 1125
30.2.2 Read-Time Concept......Page 1126
30.2.4 Experimental Verification: Grid-Like and Random Pattern......Page 1128
30.2.5 Path Trajectories with Grid-Like Pattern......Page 1130
30.2.6 Comparison with Other RFID-Based Methods......Page 1133
30.3.2 Multiple Obstacles Avoidance......Page 1134
30.3.4 Navigation with a Single Static Obstacle......Page 1137
30.3.5 Navigation with Multiple Static Obstacles......Page 1139
30.4.1 Application Concepts......Page 1141
30.4.2 Extension Possibilities......Page 1142
30.5 Conclusions......Page 1147
References......Page 1148
31.1 Introduction......Page 1149
31.1.1 VLC Systems......Page 1150
31.1.2 VLP Systems......Page 1154
31.2 Visible Light Systems Basics......Page 1155
31.2.1 Light as Carrier......Page 1156
31.2.2 Transmitter and Receiver for Visible Light Carriers......Page 1157
31.2.3 The Visible Light Channel......Page 1164
31.2.4 LOS Channel Model......Page 1165
31.2.5 Non-Line-of-Sight Channel Model......Page 1166
31.2.7 Optical Interference and Noise......Page 1167
31.2.8 Modulation Techniques for Visible Light Systems......Page 1169
31.3.2 Identity-Based Techniques......Page 1173
31.3.3 Computer Vision Techniques......Page 1175
31.3.4 Trilateration Methods and Ranging Techniques......Page 1179
31.3.5 Triangulation......Page 1181
31.3.6 Fingerprinting......Page 1184
31.4 Conclusion......Page 1185
References......Page 1187
32.1.2 Radio Access Network......Page 1193
32.1.3 Core Network......Page 1194
32.1.4 Air Interface......Page 1195
32.1.5 Advanced Antenna Systems and Beamforming......Page 1197
32.2.2 Emergency Positioning......Page 1200
32.2.3 Positioning Architecture and Signaling in LTE......Page 1201
32.3.2 User Plane......Page 1204
32.4.2 Positioning Method selection......Page 1205
32.5.1 Time......Page 1207
32.5.2 Coordinate Systems......Page 1208
32.5.3 Coordinate Transformations......Page 1209
32.6 Positioning Methods in LTE......Page 1211
32.6.2 E-CID......Page 1212
32.6.3 Fingerprinting......Page 1218
32.6.4 OTDOA......Page 1223
32.6.5 UTDOA......Page 1229
32.6.6 A-GNSS......Page 1230
32.7 Shape Conversion......Page 1232
32.8.2 Accuracy Metrics......Page 1235
32.8.3 Indoor Aspects......Page 1236
32.8.4 Expected Performance......Page 1237
References......Page 1244
33.1 Introduction......Page 1247
33.2.1 Wildlife Tag Design Constraints......Page 1248
33.2.2 Terrestrial Wildlife Transmitters......Page 1250
33.2.3 Terrestrial Wildlife Receivers......Page 1251
33.2.4 Satellite Tracking Systems......Page 1254
33.2.6 Cellular Tracking......Page 1255
33.2.8 Summary and Motivation for Improvements......Page 1256
33.3 A New Approach to Wildlife Tracking......Page 1257
33.3.2 Signal Processing......Page 1264
33.3.4 Arrival-Time Location Finding Algorithms......Page 1275
33.4.1 Testing a TOA System......Page 1280
33.5 Caveats and Limitations......Page 1286
References......Page 1287
34.1 Introduction......Page 1291
34.2 WLPS Structure......Page 1295
34.3.1 The DS-CDMA Receiver......Page 1301
34.3.2 Simulation Results......Page 1302
34.4 Adaptive Beamforming Techniques......Page 1306
34.6 WLPS Design and Structure......Page 1309
34.7 CONCLUSIONS......Page 1314
References......Page 1315
Chapter 35 Near-Ground Channel Modeling with Applications in Wireless Sensor Networks and Autonomous Driving......Page 1317
35.1 Introduction......Page 1318
35.2 Derivation of the Break Points......Page 1319
35.3.2 Medium-Range Communication......Page 1324
35.3.4 Communication in Urban Setting......Page 1327
35.4 Model Validation and WSN Connectivity Analysis......Page 1328
35.4.1 Model Validation and Discussion......Page 1329
35.4.2 Connectivity in Near-Ground WSNs......Page 1330
35.5 Conclusion......Page 1334
References......Page 1335
Index......Page 1337
IEEE Press Series on Digital and Mobile Communication......Page 1374
EULA......Page 1376