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The Resource Indoor geolocation science and technology : at the emergence of smart world and IoT, Kaveh Pahlavan

Indoor geolocation science and technology : at the emergence of smart world and IoT, Kaveh Pahlavan

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Indoor geolocation science and technology : at the emergence of smart world and IoT
Title
Indoor geolocation science and technology
Title remainder
at the emergence of smart world and IoT
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Kaveh Pahlavan
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eng
Summary
Precise and accurate localization is one of the fundamental scientific and engineering technologies needed for the applications enabling the emergence of the Smart World and the Internet of Things (IoT). Popularity of localization technology began when the GPS became open for commercial applications in early 1990's. Since most commercial localization applications are for indoors and GPS does not work indoors, the discovery of opportunistic indoor geolocation technologies began in mid-1990's. Because of complexity and diversity of science and technology involved in indoor Geolocation, this area has emerged as its own discipline over the past two decades. At the time of this writing, received signal strength (RSS) based Wi-Fi localization is dominating the commercial market complementing cell tower localization and GPS technologies using the time of arrival (TOA) technology. Wi-Fi localization technology takes advantage of the random deployment of Wi-Fi devices worldwide to support indoor and urban area localization for hundreds of thousands of applications on smart devices. Public safety and military applications demand more precise localization for first responders and military applications deploy specialized infrastructure for more precise indoor geolocation. To enhance the performance both industries are examining hybrid localization techniques. Hybrid algorithms use a variety of sensors to measure the speed and direction of movement and integrate them with the absolute radio frequency localization. Indoor Geolocation Science and Technology is a multidisciplinary book that presents the fundamentals of opportunistic localization and navigation science and technology used in different platforms such as: smart devices, unmanned ground and flying vehicles, and existing cars operating as a part of intelligent transportation systems. Material presented in the book are beneficial for the Electrical and Computer Engineering, Computer Science, Robotics Engineering, Biomedical Engineering or other disciplines who are interested in integration of navigation into their multi-disciplinary projects. The book provides examples with supporting MATLAB codes and hands-on projects throughout to improve the ability of the readers to understand and implement variety of algorithms. It can be used for both academic education, as a textbook with problem sets and projects, and the industrial training, as a practical reference book for professionals involved in design and performance evaluation. The author of this book has pioneering research experience and industrial exposure in design and performance evaluation of indoor geolocation based on empirical measurement and modeling of the behavior of the radio propagation in indoor areas and inside the human body. The presentation of the material is based on examples of research and development that his students have performed in his laboratory, his teaching experiences as a professor, and his experiences as a technical consultant to successful startup companies
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CaBNVSL
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1951-
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Pahlavan, Kaveh
Dewey number
621.3841/92
Illustrations
illustrations
Index
index present
LC call number
TK5103.4895
LC item number
.P34 2019eb
Nature of contents
  • dictionaries
  • bibliography
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  • River Publishers
  • IEEE Xplore (Online Service)
Series statement
River Publishers series in communications
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  • Geographic information systems
  • Indoor positioning systems (Wireless localization)
  • Wireless localization
  • Internet of things
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Indoor geolocation science and technology : at the emergence of smart world and IoT, Kaveh Pahlavan
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Bibliography note
Includes bibliographical references and index
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online resource
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rdacarrier
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text
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rdacontent
Contents
  • Preface xv -- 1 Introduction: Localization in SmartWorld 1 -- 1.1 Introduction 1 -- 1.2 Elements of Localization Science 3 -- 1.3 Localization Technology and Applications 6 -- 1.3.1 Localization for Smart Devices 7 -- 1.3.2 Localization for the Robots 8 -- 1.3.3 Localization in Smart Health 9 -- 1.3.4 Smart Spaces and Localization Using RFID 9 -- 1.3.5 Localization for Smart Transportation Systems 10 -- 1.3.6 Localization for Smart Infrastructure 11 -- 1.4 Some Existing Challenges in Localization 11 -- 1.5 Overview of the Book 13 Assignments for Chapter One 15 -- 2 Fundamentals of RSS Ranging 17 -- 2.1 Introduction 17 -- 2.2 Modeling RSS Behavior for Ranging 18 -- 2.2.1 LS Estimation of RSS Model Parameters 20 -- 2.2.2 NIST Model for RSS inside the Human Body 22 -- 2.2.3 IEEE 802.11 Model for Indoor Areas 24 -- 2.2.4 Okumura-Hata Model for Urban Areas 26 -- 2.2.5 Behavior of Shadow Fading and Localization Applications 27 -- 2.3 RSS-Based Ranging and Distance Measurement Error 28 -- 2.3.1 Measurement of Distance using the RSS 29 -- 2.3.2 An Analytical Method to Calculate the Variance of DME 31 -- 2.4 Classical Estimation Theory and RSS-Based Ranging 33 -- 2.4.1 ML and MMSE Estimation for RSS-Based Ranging 33 -- 2.4.2 Range Estimation with Multiple RSS Measurements 35 -- 2.4.3 CRLB for Ranging with RSS Measurement 36 -- 2.4.4 CRLB for Ranging with Multiple RSS Measurements 39 -- 2.5 Confidence Regions for RSS-Based Ranging 39 -- 2.5.1 Circular Confidence Regions for an RSS-Based Ranging 41 -- 2.5.2 Rim-Shaped Confidence Regions for RSS-Based Ranging 44 -- 2.5.3 Confidence and Probability of Coverage 46 Assignments for Chapter Two 48 -- 3 RSS Positioning Systems 53 -- 3.1 Introduction 53 -- 3.2 Performance of RSS Positioning Methods 55 -- 3.2.1 Positioning Using RSS Directly 56 -- 3.2.2 CRLB for Positioning Using RSS Directly 57 -- 3.2.3 RSS-Based Ranging Using Fingerprint 62 -- 3.2.4 CRLB for Positioning Using an RSS Fingerprint Database 64 -- 3.3 Positioning Systems Using RSS Directly 68
  • Algorithms 330-- 9.3.5 Super-Resolution Algorithm 332 9.4 DOA Estimation Using Multicarrier Signals 335 9.4.1 Spatial Filter Periodogram Algorithm 338 9.4.2 Discrete Maximum Likelihood Algorithm 341 9.5 TOA Positioning in the Absence of Direct Path 344 9.5.1 Ranging Using Multipath Diversity 345 9.5.2 RW-RLS Algorithm for Spatial Diversity 349 9.5.3 Cooperative Localization for Spatial Diversity 351 Appendix 9.A: MATLAB for Super-Resolution Algorithm (Prepared by Yunxing Ye) 353 Assignments for Chapter Nine 361 -- 10 Sensor Fusion for Hybrid Localization 365 10.1 Introduction 365 -- 10.1.1 Coordinate System for Integration 366 -- 10.1.2 Classification of Relative Location Sensors 369 10.2 Mechanical Location Sensor 370 -- 10.2.1 Accelerometer 373 -- 10.2.2 Gyroscope 374 -- 10.2.3 Odometer and Step Counter Sensor 376 -- 10.3 Magnetic Location Sensors 379 10.3.1 Gravity Sensor 379 -- 10.3.2 Magnetometer and Electronic Compass 381 -- 10.4 Environmental Location Sensors 384 -- 10.4.1 Barometer 385 10.4.2 Ambient Light, Temperature, and Humidity Sensors 387 10.4.3 Proximity Sensors and LiDAR 387 -- 10.5 Geometric Methods for Relative Positioning 388 -- 10.5.1 RF Geometric Methods 388 10.5.2 Geometric Methods Using Video Cameras 390 10.5.3 Simultaneous Localization and Mapping (SLAM) 392 10.5.4 Camera for Relative Positioning Inside the Body 392 10.6 RF Signals and Relative Positioning 396 10.6.1 Doppler Spectrum and Speed of Motion 396 10.6.2 Speed Measurement Techniques for Doppler Spectrum 400 10.7 Hybrid Algorithms for Sensor Fusion 403 10.7.1 Particle Filter for 2D Indoor Positioning of Robot 403 10.7.2 Kalman Filter for Indoor 2D Positioning of Robot 408 10.7.3 Kalman Filter for 3D In-Body Localization 411 Appendix 10.A: MATLAB Codes 417 Assignments for Chapter Ten 417 Appendix A: Review of Classical Estimation Theory for Positioning 419 A.1 Maximum Likelihood Estimation 419 A.1.1 ML Estimate of Single Observation of Parameter 420 A.1.2 ML Estimate of Function of Parameter 421 A.1.3 ML Estimate of N-Observations of Parameter 422 A.1.4 ML Estimate of N-Observation of Function of Parameter 425 A.2 Minimum Mean Square Error Estimation 427 A.2.1 MMSE Estimation of Parameter 427 A.2.2 MMSE Estimation of Function of Parameter 428 A.2.3 MMSE Estimation of N-Observations of Parameter 429 A.2.4 MMSE Estimation of N-Observations of Function of Parameter 430 A.3 Performance Analysis Using CRLB 431 A.3.1 CRLB of Single Observation of Parameter 431 A.3.2 CRLB of Observation of Function of Parameter 432 A.3.3 CRLB of N-Observation of Parameter 432 A.3.4 CRLB of N-Observation of Function of Parameter 433 A.4 CRLB of Continuous Waveforms 435 A.4.1 CRLB of Observation of Samples of Waveform 435 A.4.2 CRLB for Observation of Continuous Waveform 437 A.5 Generalization for Positioning 438 List of Abbreviations 441 List of Parameters 445 -- References 449 -- Index 465 -- About the Author 471
  • 3.3.1 RSS-Based Localization Inside the Human Body 68 -- 3.3.2 RSS-Based Passive RFID Systems 70 -- 3.3.3 RSS-Based Active RFID Systems 74 -- 3.4 Positioning Systems Using RSS Fingerprint Database 74 -- 3.4.1 RTLS Wi-Fi Positioning Using RSS Fingerprints 76 -- 3.4.2 WPS Wi-Fi Positioning Using RSS Fingerprints 79 -- 3.4.3 WPS versus GPS 82 -- 3.4.4 WPS and Organic Data 84 -- 3.4.5 CPS Cell Tower Localization Using RSS Fingerprinting 86 Assignments for Chapter Three 89 -- 4 Fundamentals of TOA Positioning 91 -- 4.1 Introduction 91 -- 4.2 Measurement of TOA in Practice 92 -- 4.2.1 NB and WB Measurement of TOA 93 -- 4.2.2 Measurement Time, Measurement Noise, and SNR 96 -- 4.2.3 Ambiguity in NB and WB TOA Measurements 101 -- 4.2.4 Using Two Sinusoids to Control NB Ambiguity 103 -- 4.3 CRLB for TOA Ranging 104 -- 4.3.1 Comparison of TOA- and RSS-Based Ranging 107 -- 4.3.2 CRLB for TOA Ranging Using the Carrier Signal 110 -- 4.3.3 CRLB for TOA Ranging Using Two Tones 111 -- 4.3.4 CRLB for TOA Ranging Using Multi-Carrier Transmission 112 -- 4.3.5 CRLB for TOA Ranging Using Pulse with Flat Spectrum 114 -- 4.3.6 CRLB for TOA Positioning 115 -- 4.4 Performance of DOA-Based Localization 117 -- 4.4.1 CRLB for DOA Estimation with Two Antennas 119 -- 4.4.2 CRLB for DOA Estimation Using an Antenna Array 121 Assignments for Chapter Four 123 -- 5 Opportunistic TOA Positioning 127 -- 5.1 Introduction 127 -- 5.1.1 Opportunistic Signals for TOA Positioning 128 -- 5.2 Pulse Transmission for TOA Positioning 130 -- 5.2.1 UWB Pulses for Opportunistic Positioning at 3.1-10.6 GHz 132 -- 5.2.2 mmWave UWB Pulses for Positioning at 57-64 BHz 136 -- 5.2.3 Pseudo DSSS Pulses for Opportunistic Positioning 138 -- 5.3 Multi-Carrier Transmission for TOA Positioning 142 -- 5.3.1 OFDM Signals for Opportunistic Positioning 143 -- 5.3.2 FHSS for Opportunistic Positioning 145 -- 5.4 Synchronization for Time-of-Flight Measurements 146 -- 5.4.1 Sliding Correlator for Time Synchronization 147 -- 5.4.2 U-TDOA for Positioning with Relative Timing 149
  • 5.4.3 Using Transponders to Avoid Synchronization 150 -- 5.5 TOA Positioning in Non-Homogeneous Environment 151 -- 5.5.1 Non-Homogeneous Medium and Differential GPS 152 -- 5.5.2 Time of Flight Inside the Non-Homogeneous Human Body 154 Assignments for Chapter Five 157 -- 6 TOA Positioning in Multipath 159 -- 6.1 Introduction 159 -- 6.2 Multipath and Positioning Systems 159 -- 6.2.1 Causes of Multipath Propagation 160 -- 6.2.2 Effects of Multipath on TOA Ranging 161 -- 6.2.3 Multipath and Positioning System Technologies 163 -- 6.2.4 Characteristics of Indoor Multipath and TOA Positioning 164 -- 6.2.5 Characteristics of Outdoor Multipath and TOA Positioning 167 -- 6.3 NB and WB Estimation of TOA in Multipath 169 -- 6.3.1 Multipath and NB TOA Ranging 171 -- 6.3.2 Multipath and WB TOA Ranging 172 -- 6.3.3 CRLB of TOA-Based Ranging in Multipath 174 -- 6.4 Measurement of Multipath Channel Characteristics 175 -- 6.4.1 Time-Domain Measurement of Multipath Arrivals 176 -- 6.4.2 Frequency-Domain Measurement of Multipath Arrivals 177 -- 6.4.3 UWB Multipath Arrivals Measurement Using VNA 177 -- 6.5 Empirical Analysis of the TOA-Based DME 179 -- 6.5.1 Empirical Analysis of the Effects of Bandwidth on DME 180 -- 6.5.2 Empirical Analysis of TOA in LOS and OLOS Conditions 182 -- 6.5.3 Empirical Analysis of the Effects of Human Body 183 -- 6.5.4 UWB Limitations for Optimal DME 184 -- 6.5.5 An Existing UWB Indoor Measurements Database at NIST 187 -- 6.6 UWB Modeling of TOA Ranging Error 187 -- 6.6.1 UWB Empirical Modeling of DME in Indoor Areas 187 -- 6.6.2 UWB Empirical Modeling of the Effects of Human Body 190 -- 6.7 Ray Tracing for In-Room RF Positioning 192 -- 6.7.1 Fundamentals of Ray Tracing for Multipath Analysis 193 -- 6.7.2 MATLAB Code for Ray Tracing Inside Room 196 -- 6.7.3 Ray Tracing and Effects of Bandwidth on TOA Ranging 198 -- 6.8 Ray Tracing for Indoor Geolocation 201 -- 6.8.1 Analysis of the Effects of Large Metallic Objects 204 -- 6.8.2 Effects of Micro Metals using Diffraction Analysis 208
  • 6.8.3 Effects of Human Body on TOA Estimation 211 -- 6.9 Computational Methods for Localization in Body Area Networks 213 -- 6.9.1 Validation of FDTD Methods for BAN Applications 214 -- 6.9.2 Validation of FEM Method for BAN Applications 217 -- 6.9.3 Modeling TOA from Inside to the Surface of the Human Body 219 Appendix 6.A 222 Appendix 6.B 225 Assignments for Chapter Six 228 -- 7 Introduction to Positioning Algorithms 235 -- 7.1 Introduction 235 -- 7.2 Basic Triangulation Methods for Positioning 237 -- 7.2.1 Triangulation Using (R, Ü) 238 -- 7.2.2 Triangulation Using (Ü; Ü) 240 -- 7.2.3 Triangulation Using (R, R) 242 -- 7.2.4 Differential Triangulation Using (ER, ER) 244 -- 7.2.5 Cooperative Triangulation 245 -- 7.3 LS Method for Positioning 247 -- 7.3.1 LS Method for Positioning with Angles 248 -- 7.3.2 LS Method for Positioning with Distances 249 -- 7.4 Practical Solutions to LS Problem 251 -- 7.4.1 RLS Algorithm for Distance-Based Positioning 253 -- 7.4.2 Residual Weighted RLS Algorithm for Indoor and Urban Areas 256 -- 7.4.3 Closest Neighbor LS Grid Algorithm 258 Appendix 7.A: MATLAB Code for RLS of Example 7.2 -- 261 Assignments for Chapter Seven 264 -- 8 RSS-Based Positioning Algorithms 269 -- 8.1 Introduction 269 -- 8.2 RSS-Based Algorithms for Short-Range Positioning 270 -- 8.2.1 Physical Grid Closest Neighbor Algorithm 271 -- 8.2.2 CNLS for RSS-Based Localization 273 -- 8.2.3 Probabilistic Grid Closest Neighbor Algorithms 275 -- 8.2.4 Maximum Likelihood Grid Triangulation Algorithm 278 -- 8.3 Pattern Recognition Algorithms for WPS 281 -- 8.3.1 Centroid Algorithm and QoE for AP Database 283 -- 8.3.2 Weighted Centroid Algorithm for Device Localization 286 -- 8.3.3 Organic Data and Positioning the Hidden APs 288 -- 8.4 Pattern Recognition Algorithms for RTLS 290 -- 8.4.1 Closest Neighbor Power Difference Algorithm 291 -- 8.4.2 K-Closest Neighbor Power Difference Algorithm 293 -- 8.4.3 Maximum Likelihood Kernel Algorithms 294
  • 8.5 Alternatives to Manual Indoor Fingerprinting 297 -- 8.5.1 Ray tracing for Fingerprinting Algorithms 298 -- 8.5.2 Modified IEEE 802.11 Model for Fingerprinting 299 -- 8.5.3 Robots to Collect RF Fingerprints 303 -- 8.6 Pattern Recognition Algorithms for the CPS 304 Appendix 8.A: MATLAB Code for ML Triangulation Grid Algorithm 307 Appendix 8.B: MATLAB Code for Simple Kernel Algorithm 309 Assignments for Chapter Eight 310 -- 9 TOA-Based Positioning Algorithms 315 -- 9.1 Introduction 315 -- 9.2 Basic Algorithms for Measurement of TOA 316 -- 9.2.1 NB TOA Estimation Algorithms and Multipath 316 -- 9.2.2 WB TOA Estimation Algorithms and Multipath 320 -- 9.3 TOA Estimation Algorithms for Multicarrier Signals 322 -- 9.3.1 RLS Algorithm for Multicarrier Ranging in Multipath 322 -- 9.3.2 Peak Detection IFT Algorithm 325 -- 9.3.3 Effects of Multipath on Peak Detection IFT Algorithm 328 -- 9.3.4 Spectral Estimation
Control code
9218820
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unknown
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1 PDF (xix, 471 pages).
Form of item
online
Governing access note
Restricted to subscribers or individual electronic text purchasers
Isbn
9788770220507
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electronic
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isbdmedia
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remote
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  • (CaBNVSL)mat09218820
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Mode of access: World Wide Web
Label
Indoor geolocation science and technology : at the emergence of smart world and IoT, Kaveh Pahlavan
Publication
Distribution
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier MARC source
rdacarrier
Content category
text
Content type MARC source
rdacontent
Contents
  • Preface xv -- 1 Introduction: Localization in SmartWorld 1 -- 1.1 Introduction 1 -- 1.2 Elements of Localization Science 3 -- 1.3 Localization Technology and Applications 6 -- 1.3.1 Localization for Smart Devices 7 -- 1.3.2 Localization for the Robots 8 -- 1.3.3 Localization in Smart Health 9 -- 1.3.4 Smart Spaces and Localization Using RFID 9 -- 1.3.5 Localization for Smart Transportation Systems 10 -- 1.3.6 Localization for Smart Infrastructure 11 -- 1.4 Some Existing Challenges in Localization 11 -- 1.5 Overview of the Book 13 Assignments for Chapter One 15 -- 2 Fundamentals of RSS Ranging 17 -- 2.1 Introduction 17 -- 2.2 Modeling RSS Behavior for Ranging 18 -- 2.2.1 LS Estimation of RSS Model Parameters 20 -- 2.2.2 NIST Model for RSS inside the Human Body 22 -- 2.2.3 IEEE 802.11 Model for Indoor Areas 24 -- 2.2.4 Okumura-Hata Model for Urban Areas 26 -- 2.2.5 Behavior of Shadow Fading and Localization Applications 27 -- 2.3 RSS-Based Ranging and Distance Measurement Error 28 -- 2.3.1 Measurement of Distance using the RSS 29 -- 2.3.2 An Analytical Method to Calculate the Variance of DME 31 -- 2.4 Classical Estimation Theory and RSS-Based Ranging 33 -- 2.4.1 ML and MMSE Estimation for RSS-Based Ranging 33 -- 2.4.2 Range Estimation with Multiple RSS Measurements 35 -- 2.4.3 CRLB for Ranging with RSS Measurement 36 -- 2.4.4 CRLB for Ranging with Multiple RSS Measurements 39 -- 2.5 Confidence Regions for RSS-Based Ranging 39 -- 2.5.1 Circular Confidence Regions for an RSS-Based Ranging 41 -- 2.5.2 Rim-Shaped Confidence Regions for RSS-Based Ranging 44 -- 2.5.3 Confidence and Probability of Coverage 46 Assignments for Chapter Two 48 -- 3 RSS Positioning Systems 53 -- 3.1 Introduction 53 -- 3.2 Performance of RSS Positioning Methods 55 -- 3.2.1 Positioning Using RSS Directly 56 -- 3.2.2 CRLB for Positioning Using RSS Directly 57 -- 3.2.3 RSS-Based Ranging Using Fingerprint 62 -- 3.2.4 CRLB for Positioning Using an RSS Fingerprint Database 64 -- 3.3 Positioning Systems Using RSS Directly 68
  • Algorithms 330-- 9.3.5 Super-Resolution Algorithm 332 9.4 DOA Estimation Using Multicarrier Signals 335 9.4.1 Spatial Filter Periodogram Algorithm 338 9.4.2 Discrete Maximum Likelihood Algorithm 341 9.5 TOA Positioning in the Absence of Direct Path 344 9.5.1 Ranging Using Multipath Diversity 345 9.5.2 RW-RLS Algorithm for Spatial Diversity 349 9.5.3 Cooperative Localization for Spatial Diversity 351 Appendix 9.A: MATLAB for Super-Resolution Algorithm (Prepared by Yunxing Ye) 353 Assignments for Chapter Nine 361 -- 10 Sensor Fusion for Hybrid Localization 365 10.1 Introduction 365 -- 10.1.1 Coordinate System for Integration 366 -- 10.1.2 Classification of Relative Location Sensors 369 10.2 Mechanical Location Sensor 370 -- 10.2.1 Accelerometer 373 -- 10.2.2 Gyroscope 374 -- 10.2.3 Odometer and Step Counter Sensor 376 -- 10.3 Magnetic Location Sensors 379 10.3.1 Gravity Sensor 379 -- 10.3.2 Magnetometer and Electronic Compass 381 -- 10.4 Environmental Location Sensors 384 -- 10.4.1 Barometer 385 10.4.2 Ambient Light, Temperature, and Humidity Sensors 387 10.4.3 Proximity Sensors and LiDAR 387 -- 10.5 Geometric Methods for Relative Positioning 388 -- 10.5.1 RF Geometric Methods 388 10.5.2 Geometric Methods Using Video Cameras 390 10.5.3 Simultaneous Localization and Mapping (SLAM) 392 10.5.4 Camera for Relative Positioning Inside the Body 392 10.6 RF Signals and Relative Positioning 396 10.6.1 Doppler Spectrum and Speed of Motion 396 10.6.2 Speed Measurement Techniques for Doppler Spectrum 400 10.7 Hybrid Algorithms for Sensor Fusion 403 10.7.1 Particle Filter for 2D Indoor Positioning of Robot 403 10.7.2 Kalman Filter for Indoor 2D Positioning of Robot 408 10.7.3 Kalman Filter for 3D In-Body Localization 411 Appendix 10.A: MATLAB Codes 417 Assignments for Chapter Ten 417 Appendix A: Review of Classical Estimation Theory for Positioning 419 A.1 Maximum Likelihood Estimation 419 A.1.1 ML Estimate of Single Observation of Parameter 420 A.1.2 ML Estimate of Function of Parameter 421 A.1.3 ML Estimate of N-Observations of Parameter 422 A.1.4 ML Estimate of N-Observation of Function of Parameter 425 A.2 Minimum Mean Square Error Estimation 427 A.2.1 MMSE Estimation of Parameter 427 A.2.2 MMSE Estimation of Function of Parameter 428 A.2.3 MMSE Estimation of N-Observations of Parameter 429 A.2.4 MMSE Estimation of N-Observations of Function of Parameter 430 A.3 Performance Analysis Using CRLB 431 A.3.1 CRLB of Single Observation of Parameter 431 A.3.2 CRLB of Observation of Function of Parameter 432 A.3.3 CRLB of N-Observation of Parameter 432 A.3.4 CRLB of N-Observation of Function of Parameter 433 A.4 CRLB of Continuous Waveforms 435 A.4.1 CRLB of Observation of Samples of Waveform 435 A.4.2 CRLB for Observation of Continuous Waveform 437 A.5 Generalization for Positioning 438 List of Abbreviations 441 List of Parameters 445 -- References 449 -- Index 465 -- About the Author 471
  • 3.3.1 RSS-Based Localization Inside the Human Body 68 -- 3.3.2 RSS-Based Passive RFID Systems 70 -- 3.3.3 RSS-Based Active RFID Systems 74 -- 3.4 Positioning Systems Using RSS Fingerprint Database 74 -- 3.4.1 RTLS Wi-Fi Positioning Using RSS Fingerprints 76 -- 3.4.2 WPS Wi-Fi Positioning Using RSS Fingerprints 79 -- 3.4.3 WPS versus GPS 82 -- 3.4.4 WPS and Organic Data 84 -- 3.4.5 CPS Cell Tower Localization Using RSS Fingerprinting 86 Assignments for Chapter Three 89 -- 4 Fundamentals of TOA Positioning 91 -- 4.1 Introduction 91 -- 4.2 Measurement of TOA in Practice 92 -- 4.2.1 NB and WB Measurement of TOA 93 -- 4.2.2 Measurement Time, Measurement Noise, and SNR 96 -- 4.2.3 Ambiguity in NB and WB TOA Measurements 101 -- 4.2.4 Using Two Sinusoids to Control NB Ambiguity 103 -- 4.3 CRLB for TOA Ranging 104 -- 4.3.1 Comparison of TOA- and RSS-Based Ranging 107 -- 4.3.2 CRLB for TOA Ranging Using the Carrier Signal 110 -- 4.3.3 CRLB for TOA Ranging Using Two Tones 111 -- 4.3.4 CRLB for TOA Ranging Using Multi-Carrier Transmission 112 -- 4.3.5 CRLB for TOA Ranging Using Pulse with Flat Spectrum 114 -- 4.3.6 CRLB for TOA Positioning 115 -- 4.4 Performance of DOA-Based Localization 117 -- 4.4.1 CRLB for DOA Estimation with Two Antennas 119 -- 4.4.2 CRLB for DOA Estimation Using an Antenna Array 121 Assignments for Chapter Four 123 -- 5 Opportunistic TOA Positioning 127 -- 5.1 Introduction 127 -- 5.1.1 Opportunistic Signals for TOA Positioning 128 -- 5.2 Pulse Transmission for TOA Positioning 130 -- 5.2.1 UWB Pulses for Opportunistic Positioning at 3.1-10.6 GHz 132 -- 5.2.2 mmWave UWB Pulses for Positioning at 57-64 BHz 136 -- 5.2.3 Pseudo DSSS Pulses for Opportunistic Positioning 138 -- 5.3 Multi-Carrier Transmission for TOA Positioning 142 -- 5.3.1 OFDM Signals for Opportunistic Positioning 143 -- 5.3.2 FHSS for Opportunistic Positioning 145 -- 5.4 Synchronization for Time-of-Flight Measurements 146 -- 5.4.1 Sliding Correlator for Time Synchronization 147 -- 5.4.2 U-TDOA for Positioning with Relative Timing 149
  • 5.4.3 Using Transponders to Avoid Synchronization 150 -- 5.5 TOA Positioning in Non-Homogeneous Environment 151 -- 5.5.1 Non-Homogeneous Medium and Differential GPS 152 -- 5.5.2 Time of Flight Inside the Non-Homogeneous Human Body 154 Assignments for Chapter Five 157 -- 6 TOA Positioning in Multipath 159 -- 6.1 Introduction 159 -- 6.2 Multipath and Positioning Systems 159 -- 6.2.1 Causes of Multipath Propagation 160 -- 6.2.2 Effects of Multipath on TOA Ranging 161 -- 6.2.3 Multipath and Positioning System Technologies 163 -- 6.2.4 Characteristics of Indoor Multipath and TOA Positioning 164 -- 6.2.5 Characteristics of Outdoor Multipath and TOA Positioning 167 -- 6.3 NB and WB Estimation of TOA in Multipath 169 -- 6.3.1 Multipath and NB TOA Ranging 171 -- 6.3.2 Multipath and WB TOA Ranging 172 -- 6.3.3 CRLB of TOA-Based Ranging in Multipath 174 -- 6.4 Measurement of Multipath Channel Characteristics 175 -- 6.4.1 Time-Domain Measurement of Multipath Arrivals 176 -- 6.4.2 Frequency-Domain Measurement of Multipath Arrivals 177 -- 6.4.3 UWB Multipath Arrivals Measurement Using VNA 177 -- 6.5 Empirical Analysis of the TOA-Based DME 179 -- 6.5.1 Empirical Analysis of the Effects of Bandwidth on DME 180 -- 6.5.2 Empirical Analysis of TOA in LOS and OLOS Conditions 182 -- 6.5.3 Empirical Analysis of the Effects of Human Body 183 -- 6.5.4 UWB Limitations for Optimal DME 184 -- 6.5.5 An Existing UWB Indoor Measurements Database at NIST 187 -- 6.6 UWB Modeling of TOA Ranging Error 187 -- 6.6.1 UWB Empirical Modeling of DME in Indoor Areas 187 -- 6.6.2 UWB Empirical Modeling of the Effects of Human Body 190 -- 6.7 Ray Tracing for In-Room RF Positioning 192 -- 6.7.1 Fundamentals of Ray Tracing for Multipath Analysis 193 -- 6.7.2 MATLAB Code for Ray Tracing Inside Room 196 -- 6.7.3 Ray Tracing and Effects of Bandwidth on TOA Ranging 198 -- 6.8 Ray Tracing for Indoor Geolocation 201 -- 6.8.1 Analysis of the Effects of Large Metallic Objects 204 -- 6.8.2 Effects of Micro Metals using Diffraction Analysis 208
  • 6.8.3 Effects of Human Body on TOA Estimation 211 -- 6.9 Computational Methods for Localization in Body Area Networks 213 -- 6.9.1 Validation of FDTD Methods for BAN Applications 214 -- 6.9.2 Validation of FEM Method for BAN Applications 217 -- 6.9.3 Modeling TOA from Inside to the Surface of the Human Body 219 Appendix 6.A 222 Appendix 6.B 225 Assignments for Chapter Six 228 -- 7 Introduction to Positioning Algorithms 235 -- 7.1 Introduction 235 -- 7.2 Basic Triangulation Methods for Positioning 237 -- 7.2.1 Triangulation Using (R, Ü) 238 -- 7.2.2 Triangulation Using (Ü; Ü) 240 -- 7.2.3 Triangulation Using (R, R) 242 -- 7.2.4 Differential Triangulation Using (ER, ER) 244 -- 7.2.5 Cooperative Triangulation 245 -- 7.3 LS Method for Positioning 247 -- 7.3.1 LS Method for Positioning with Angles 248 -- 7.3.2 LS Method for Positioning with Distances 249 -- 7.4 Practical Solutions to LS Problem 251 -- 7.4.1 RLS Algorithm for Distance-Based Positioning 253 -- 7.4.2 Residual Weighted RLS Algorithm for Indoor and Urban Areas 256 -- 7.4.3 Closest Neighbor LS Grid Algorithm 258 Appendix 7.A: MATLAB Code for RLS of Example 7.2 -- 261 Assignments for Chapter Seven 264 -- 8 RSS-Based Positioning Algorithms 269 -- 8.1 Introduction 269 -- 8.2 RSS-Based Algorithms for Short-Range Positioning 270 -- 8.2.1 Physical Grid Closest Neighbor Algorithm 271 -- 8.2.2 CNLS for RSS-Based Localization 273 -- 8.2.3 Probabilistic Grid Closest Neighbor Algorithms 275 -- 8.2.4 Maximum Likelihood Grid Triangulation Algorithm 278 -- 8.3 Pattern Recognition Algorithms for WPS 281 -- 8.3.1 Centroid Algorithm and QoE for AP Database 283 -- 8.3.2 Weighted Centroid Algorithm for Device Localization 286 -- 8.3.3 Organic Data and Positioning the Hidden APs 288 -- 8.4 Pattern Recognition Algorithms for RTLS 290 -- 8.4.1 Closest Neighbor Power Difference Algorithm 291 -- 8.4.2 K-Closest Neighbor Power Difference Algorithm 293 -- 8.4.3 Maximum Likelihood Kernel Algorithms 294
  • 8.5 Alternatives to Manual Indoor Fingerprinting 297 -- 8.5.1 Ray tracing for Fingerprinting Algorithms 298 -- 8.5.2 Modified IEEE 802.11 Model for Fingerprinting 299 -- 8.5.3 Robots to Collect RF Fingerprints 303 -- 8.6 Pattern Recognition Algorithms for the CPS 304 Appendix 8.A: MATLAB Code for ML Triangulation Grid Algorithm 307 Appendix 8.B: MATLAB Code for Simple Kernel Algorithm 309 Assignments for Chapter Eight 310 -- 9 TOA-Based Positioning Algorithms 315 -- 9.1 Introduction 315 -- 9.2 Basic Algorithms for Measurement of TOA 316 -- 9.2.1 NB TOA Estimation Algorithms and Multipath 316 -- 9.2.2 WB TOA Estimation Algorithms and Multipath 320 -- 9.3 TOA Estimation Algorithms for Multicarrier Signals 322 -- 9.3.1 RLS Algorithm for Multicarrier Ranging in Multipath 322 -- 9.3.2 Peak Detection IFT Algorithm 325 -- 9.3.3 Effects of Multipath on Peak Detection IFT Algorithm 328 -- 9.3.4 Spectral Estimation
Control code
9218820
Dimensions
unknown
Extent
1 PDF (xix, 471 pages).
Form of item
online
Governing access note
Restricted to subscribers or individual electronic text purchasers
Isbn
9788770220507
Media category
electronic
Media MARC source
isbdmedia
Specific material designation
remote
System control number
  • (CaBNVSL)mat09218820
  • (IDAMS)0b0000648d199fd9
System details
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