Multi-Technology Positioning (eBook)

Jari Nurmi works as a Professor at Tampere University of Technology, Finland since 1999, in the Faculty of Computing and Electrical Engineering. He is working on embedded computing systems, wireless localization, positioning receiver prototyping, and software-defined radio. He held various research, education and management positions at TUT since 1987 and was the Vice President of the SME VLSI Solution Oy 1995-1998. Since 2013 he is also a partner and co-founder of Ekin Labs Oy, a research spin-off company commercializing technology for human presence detection, now headquartered in Silicon Valley as Radiomaze, Inc. He has supervised 19 PhD and over 130 MSc theses at TUT, and been the opponent or reviewer of 32 PhD theses for other universities worldwide. He is a senior member of IEEE, member of the technical committee on VLSI Systems and Applications at IEEE CAS, and board member of Tampere Convention Bureau. In 2011 he received IIDA Innovation Award, and in 2013 the Scientific Congress Award and HiPEAC Technology Transfer Award. He is a steering committee member of four international conferences, in the chairman position in two. He has edited 5 Springer books, and has published about 350 international conference and journal articles and book chapters. He has participated in the Marie Curie ITN network MULTI-POS as the network coordinator and scientist in charge.Elena-Simona Lohan is an Associate Professor at the Department of Electronics and Communication Engineering at Tampere University of Technology (TUT). She is also a Visiting Professor at Universitat Autònoma de Barcelona, Spain. She received an M.Sc. degree in Electrical Engineering from Polytechnics University of Bucharest, Romania, in 1997, a D.E.A. degree (French equivalent of master) in Econometrics, at ´ Ecole Polytechnique, Paris, France, in 1998, and a Ph.D. degree in Telecommunications from TUT, in 2003. She has more than 170 international publications, 3 patents and 2 patent applications. She is serving as Associate Editor to IET Radar, Sonar and Navigation journal and to RIN Cambridge Journal of Navigation since 2013. Her current research interests include wireless location techniques based on signals of opportunity and cognitive spectrum sensing for positioning purposes. She has participated in the Marie Curie ITN network MULTI-POS as scientist in charge and equality officer.Henk Wymeersch is a Professor in Communication Systems with the Department of Signals and Systems at Chalmers University of Technology, Sweden. Prior to joining Chalmers, he was a postdoctoral researcher from 2005 until 2009 with the Laboratory for Information and Decision Systems at the Massachusetts Institute of Technology. Henk Wymeersch obtained the Ph.D. degree in Electrical Engineering/Applied sciences in 2005 from Ghent University, Belgium. He served as Associate Editor for IEEE Communication Letters (2009-2013), IEEE Transactions on Wireless Communications (since 2013), and IEEE Transactions on Communications (since 2016). His current research interests include cooperative systems and intelligent transportation. He has participated in the Marie Curie ITN network MULTI-POS as scientist in charge.Gonzalo Seco-Granados received the PhD degree on Telecommunications Engineering from Universitat Politècnica de Catalunya in 2000 and an MBA from IESE in 2002. From 2002 to 2005, he was member of the technical staff the European Space Agency, involved in the design of the Galileo system. Since 2006, he is Associate Professor at the Department of Telecommunications, Universitat Autònoma de Barcelona. He has been principal investigator of over 25 research projects. In 2014, he received an ICREA Academia fellowship. In 2015, he wasFulbright Visiting Scholar at University of California, Irvine. His research interests include the design of signals and reception techniques for satellite-based and terrestrial positioning systems, multi-antenna receivers and signal-level integrity. He has participated in the Marie Curie ITN network MULTI-POS as scientist in charge.Ossi Nykänen works for M-Files, helping enterprises find, share, and secure documents and information. Dr. O. Nykänen also serves as an Adjunct Professor at Tampere University of Technology, Department of Mathematics. His long-term research interests include semantic computing, machine learning, information modeling and visualization, (computer-supported) mathematics, and the related applications. He is affiliated with many industrial and academic research networks, and is an advocate of international web standards. He has participated in the Marie Curie ITN network MULTI-POS as scientist in charge.

Preface 5
Acknowledgements 7
Contents 8
1 Introduction and Book Structure 10
References 13
2 MULTI-POS: Multi-Technology Positioning Professionals Training Network 14
2.1 How Everything Has Started 14
2.2 MULTI-POS Aims and Structure 15
2.3 Main Results and a Look Ahead 18
3 Understanding the GNSS Signal Model 21
3.1 Introduction 21
3.2 Signal Model Basics 22
3.2.1 Passband Signal Model 23
3.2.2 Baseband Signal Model 26
3.3 Signal-to-Noise and Carrier-to-Noise Density Ratios 31
3.4 Noise in Computer Simulation 35
3.4.1 From Baseband to Passband and Back 37
3.4.2 Noise Correlation 41
3.4.3 Simulation Setup 44
3.5 The Doppler Effect 45
3.5.1 The Doppler Effect Fundamentals 46
3.5.1.1 Static Transmitter and Moving Receiver 47
3.5.1.2 Moving Transmitter and Static Receiver 49
3.5.1.3 Considering the Special Relativity 51
3.5.2 Practical Values of the Doppler Shift in gnss 53
3.5.3 Impact of the Doppler Effect on the Received Signal 56
3.5.4 gnss Signal Model Revision 57
3.6 Conclusions 59
References 60
4 GNSS Vulnerabilities 62
4.1 Introduction and Motivation 62
4.2 Ionospheric Error 65
4.2.1 What is the Ionospheric Error? 65
4.2.2 Ionospheric Error Mitigation 66
4.2.2.1 Dual Frequency Combination 66
4.2.2.2 Physics-Based Data Driven Ionospheric Models 66
4.2.2.3 Ionospheric Maps 66
4.2.2.4 Ionospheric Data Driven Models 67
4.3 Multipath 67
4.3.1 Impact of Multipath on Code Measurements 69
4.3.2 Impact of Multipath on Carrier Phase Measurements 69
4.3.3 Impact of Multipath on Signal Strength and Doppler Frequency Measurements 70
4.3.4 System Sensitivity to Multipath 71
4.3.5 Multipath Mitigation 71
4.3.5.1 Correlation-Based Mitigation 71
4.3.5.2 Measurement-Based Mitigation 72
4.3.5.3 Hardware Mitigation 72
4.3.5.4 Other Types of Mitigation 73
4.3.6 Multipath Detection Without Mitigation 73
4.4 Radio Frequency Interference in GNSS 73
4.4.1 Unintentional RF Interference 74
4.4.1.1 Commercial Broadcasting Interference 74
4.4.2 Intentional RF Interference 76
4.4.2.1 Jamming 76
4.4.2.2 Spoofing 77
4.4.3 Interference Countermeasures 77
4.4.3.1 Interference Detection 78
4.4.3.2 Interference Mitigation 79
4.5 Conclusions 80
References 81
5 GNSS Quality of Service in Urban Environment 85
5.1 Conventional gnss Signal Tracking 85
5.1.1 Code Tracking Loop 88
5.1.2 Carrier Tracking Loop 91
5.2 Problematic in Urban Environment 93
5.3 Advanced Signal Processing 94
5.3.1 gnss nlos Rejection Technique 94
5.3.2 vt Technique 95
5.3.2.1 vdfll ekf State Model 97
5.3.2.2 vdfll ekf Observation Model 99
5.3.2.3 vdfll Estimation Workflow 100
5.3.2.4 Performed Tests in Urban Conditions 101
5.4 Carrier Phase Measurements in Urban Environments 104
5.5 Conclusions 109
References 110
6 Multi-GNSS: Facts and Issues 112
6.1 Introduction 112
6.2 Global Navigation Satellite Systems 113
6.2.1 GPS 113
6.2.1.1 Space Segment 114
6.2.1.2 Current and Planned Signals 114
6.2.1.3 Time and Geodetic Reference Frame 116
6.2.2 GLONASS 117
6.2.2.1 Space Segment 118
6.2.2.2 Current and Planned Signals 118
6.2.2.3 Time Scale and Geodetic Reference Frame 119
6.2.3 Galileo 120
6.2.3.1 Space Segment 121
6.2.3.2 Current and Planned Signals 121
6.2.3.3 Time Scale and Geodetic Reference Frame 122
6.2.4 BeiDou 123
6.2.4.1 Space Segment 124
6.2.4.2 Current and Planned Signals 124
6.2.4.3 Time Scale and Geodetic Reference Frame 125
6.3 Multi-GNSS Benefits 125
6.4 Multi-GNSS Issues 126
6.5 Conclusions 127
References 128
7 Towards Seamless Navigation 130
7.1 Introduction and Motivation 130
7.2 Adaptability 131
7.2.1 Configurational Flexibility 131
7.2.2 Environmental Adaptability 132
7.3 Context 133
7.3.1 Location 133
7.3.2 Behaviour 134
7.4 Sensors 135
7.4.1 Maps and Infrastructure 136
7.4.2 Odometers and Tactile Sensors 137
7.4.3 Sound and Pressure 138
7.4.4 Inertial Sensors 139
7.4.5 GNSS, Pseudolite and Broadcast Signals 140
7.4.6 WiFi, Bluetooth and Ultra-Wideband 141
7.4.7 Magnetic Sensors 142
7.4.8 Visible and Infrared Light Sensors 143
7.5 Sensor Fusion 145
7.5.1 Estimation 146
7.5.2 Classification 147
7.5.3 Inference 148
7.6 Conclusions 149
References 150
8 Mapping the Radio World to Find Us 153
8.1 Introduction 153
8.1.1 Opportunities 154
8.1.2 Overview 155
8.2 From Power to Distance 156
8.2.1 Non-free Space Loss 156
8.2.2 Propagation Impairments 156
8.2.3 ITU-R Model 157
8.2.4 Log-Distance Model 158
8.2.5 Typical Values 158
8.3 Fingerprinting 160
8.3.1 Learning Phase 160
8.3.1.1 Building the learning database 160
8.3.2 Online Phase 163
8.3.3 A Simple Example 163
8.3.4 Shortcomings 165
8.3.4.1 Consistency 165
8.3.4.2 Storage 165
8.3.4.3 Privacy 166
8.3.4.4 Hardware 166
8.4 Conclusions 166
References 167
9 Survey on 5G Positioning 169
9.1 Introduction 169
9.2 The Relation Between 5G and Cognitive Radio for Localization 172
9.3 On 5G Systems 172
9.3.1 Mm-Wave 172
9.3.2 Massive MIMO 173
9.3.3 Device-Centric Architecture 173
9.3.3.1 Device-Centric and Cell-Centric Positioning 175
9.3.4 D2D Communication 175
9.3.4.1 Device Relaying Communication with Base Station Controlled Link 175
9.3.4.2 Direct Device-to-Device Communication with Base Station Controlled Link 175
9.3.4.3 Device Relaying Communication with Device Controlled Link 175
9.3.4.4 Direct Device-to-Device Communication with Device Controlled Link 176
9.3.5 Location-Aware Communications 176
9.3.6 Ultra Dense Networks 177
9.3.6.1 Mobility Management in Ultra Dense Networks 177
9.4 Mm-Wave Channels 177
9.4.1 Path-Loss 178
9.4.1.1 Frequency Dependent Path-Loss 178
9.4.1.2 Geometry Based Statistical Path-Loss 178
9.4.2 Mm-Wave mimo Channel Model 179
9.4.3 Parameter Estimation 181
9.4.3.1 SAGE 181
9.4.3.2 RIMAX 181
9.4.4 Sparsity 181
9.5 Multi-Beam Transmission 184
9.5.1 Hybrid Beamformers 185
9.5.2 Beam Training Protocols 186
9.6 Localization Based on Delay, AOA, and AOD 187
9.6.1 General Localization Techniques 187
9.6.1.1 Localization Using Range Measurements 187
9.6.1.2 Localization Using Range-Difference Measurements 188
9.6.1.3 Triangulation 189
9.6.1.4 Fingerprinting 190
9.6.2 Mm-Wave Localization Techniques 190
9.7 Simulation Results 192
9.7.1 Simulation Setup 193
9.7.2 Results and Discussion 194
9.8 Conclusions 195
References 198
10 Formation Control of Multi-Agent Systems with Location Uncertainty 201
10.1 Introduction 201
10.2 Localisation for Communication and Control 203
10.2.1 Inter-Agent Communication 203
10.2.2 Multi-Agent Control 204
10.2.3 Bounding Uncertainty of Estimators: The Cramér-Rao Bound 204
10.3 Impact of Location Uncertainty on Mission Goals 205
10.3.1 Limiting Location Uncertainty 205
10.3.1.1 Problem Formulation 205
10.3.1.2 Optimisation Formulation 207
10.3.1.3 Performance Evaluation 207
10.3.2 Location-Aware Formation Control 208
10.3.2.1 Problem Formulation 208
10.3.2.2 Optimisation Formulation 210
10.3.2.3 Performance Evaluation 212
10.4 Impact of Location Uncertainty on Channel Gain Prediction 213
10.4.1 Problem Formulation 213
10.4.2 Channel Prediction 214
10.4.3 Performance Evaluation 215
10.4.3.1 Learning 215
10.4.3.2 Prediction 216
10.5 Conclusion 217
References 217
11 Positioning Technology Applications Relatedto Environmental Issues 220
11.1 Introduction 220
11.2 Definitions 220
11.3 Environmental Issues 222
11.4 Geographic Information Systems 225
11.5 Example of Environmental Applications of the Satellite Remote Sensing 227
11.5.1 Land Monitoring 227
11.5.2 Ocean and Coastal Zones 228
11.5.3 Biodiversity 229
11.5.4 Telemetry Techniques for Monitoring Animals 230
11.5.4.1 GPS Tracking 231
11.5.4.2 Argos Satellite Tracking 231
11.5.4.3 Very High Frequency Radio Tracking 231
11.5.4.4 Acoustic Tracking 232
11.5.4.5 Passive Integrated Transponder 232
11.5.4.6 Combination of Tracking Technologies 232
11.5.5 Illegal Fishing 232
11.5.6 Poaching Combat 233
11.5.7 Dealing with Natural Hazards 234
11.5.8 Marine Debris 234
11.6 European Space Agency: Earth Observation Programs 235
11.7 The COPERNICUS Program 238
11.7.1 Satellite Equipment and Contributing Missions 239
11.7.2 Sentinels 242
11.7.3 Copernicus Data Access 247
11.8 Advantages and Limitation of GIS and RS 247
11.9 Summary 248
References 249
12 Context Awareness for Semantic Mobile Computing 253
12.1 Introduction 253
12.1.1 Motivation 253
12.1.2 Background 254
12.2 Context Engine 255
12.2.1 Architecture 255
12.2.2 Responsibilities 256
12.2.3 Context Ontology 256
12.2.4 Context Queries 257
12.3 Methods for Acquiring Contextual Attributes 259
12.3.1 Case 1: Inferring User Location Based on Phone Usage 259
12.3.1.1 Dataset 259
12.3.1.2 Data Processing 260
12.3.1.3 Methods and Results 261
12.3.2 Context Inference in Social Network Settings 261
12.3.2.1 Quantifying Homophily 263
12.3.2.2 Using Homophily to Improve Predictions 264
12.3.2.3 Experiment 265
12.4 Applications Areas 266
12.5 Conclusions 267
References 268
13 The Impact of Galileo Open Service on the Location Based Services Markets: A Review on the Cost Structure and the Potential Revenue Streams 270
13.1 Introduction 270
13.2 Galileo Cost Structure and Skepticism 272
13.3 Galileo Potential Revenue Streams and Opportunities 274
13.4 Conclusions 281
References 281
14 Location Based Services Analysis Through Analytical Hierarchical Processes: An e-Health-Based Case Study 283
14.1 Introduction 283
14.1.1 Motivation 283
14.1.2 Key Questions Related to Location Based Services 286
14.1.3 Some Definitions and Introductory Concepts 288
14.2 What is an Analytical Hierarchical Process? 289
14.3 Technologies Which Can Be Used for Positioning 291
14.3.1 Wearable Technologies 291
14.3.2 Device-Free Technologies 293
14.3.3 Examples of Indoor Positioning Technologies 294
14.4 Simplified Example of Applying AHP in the e-Health LBS Context 294
14.5 Multi-Level and Joint Decisions 297
14.6 Conclusions 298
References 298
15 DroneAlert: Autonomous Drones for Emergency Response 302
15.1 Unmanned Air Vehicles 302
15.1.1 Types of uav 302
15.1.2 Laws and Regulations for Unmanned Air Vehicles 304
15.1.2.1 Privacy Considerations 304
15.1.2.2 Airspace Flight Restrictions 304
15.1.2.3 Flying License and Aircraft Registration 305
15.1.3 Current and Future Fields of Application 306
15.1.4 Components 306
15.2 Emergency Response 308
15.2.1 Sources of Emergency Alerts 308
15.2.2 Types of Emergency Situations 309
15.3 The DroneAlert System 309
15.3.1 Autonomous uavs 310
15.3.2 UAV Limitations 311
15.4 System Architecture 312
15.4.1 Components 312
15.4.1.1 Emergency Management System 313
15.4.1.2 UAV Ground Control System 313
15.4.1.3 uav Base Station Operator 314
15.4.1.4 uav 314
15.4.1.5 Mission Control Center Operator 314
15.4.2 Activities 315
15.4.2.1 Request Nearest Available uav 315
15.4.2.2 Calculate Optimal Flight Route 315
15.4.2.3 Send UAV on Mission 318
15.4.2.4 Acquire UAV Telemetry 318
15.4.2.5 Send UAV Imagery to Emergency Services 318
15.4.2.6 Return UAV from Mission 319
15.5 Conclusions 319
References 320
16 MULTI-POS: Lessons Learnt from Fellows and Supervisors 321
16.1 Introduction 321
16.2 Administrative Issues 322
16.3 Scientific Issues 324
16.4 Personal and Cultural Issues 325
16.5 Summary 327
17 Conclusions 328
About the Editors 330
Acronyms 332
Index 338