A handbook on recent advancements and the state of the art in array processing and sensor Networks Handbook on Array Processing and Sensor Networks provides readers with a collection of tutorial articles contributed by world-renowned experts on recent advancements and the state of the art in array processing and sensor networks.
Focusing on fundamental principles as well as applications, the handbook provides exhaustive coverage of: wavelets; spatial spectrum estimation; MIMO radio propagation; robustness issues in sensor array processing; wireless communications and sensing in multi-path environments using multi-antenna transceivers; implicit training and array processing for digital communications systems; unitary design of radar waveform diversity sets; acoustic array processing for speech enhancement; acoustic beamforming for hearing aid applications; undetermined blind source separation using acoustic arrays; array processing in astronomy; digital 3D/4D ultrasound imaging technology; self-localization of sensor networks; multi-target tracking and classification in collaborative sensor networks via sequential Monte Carlo; energy-efficient decentralized estimation; sensor data fusion with application to multi-target tracking; distributed algorithms in sensor networks; cooperative communications; distributed source coding; network coding for sensor networks; information-theoretic studies of wireless networks; distributed adaptive learning mechanisms; routing for statistical inference in sensor networks; spectrum estimation in cognitive radios; nonparametric techniques for pedestrian tracking in wireless local area networks; signal processing and networking via the theory of global games; biochemical transport modeling, estimation, and detection in realistic environments; and security and privacy for sensor networks.
Handbook on Array Processing and Sensor Networks is the first book of its kind and will appeal to researchers, professors, and graduate students in array processing, sensor networks, advanced signal processing, and networking.
Author(s): Simon Haykin, K. J. Ray Liu
Series: Adaptive and Learning Systems for Signal Processing, Communications and Control
Edition: 1. Auflage
Publisher: Wiley-IEEE Press
Year: 2010
Language: English
Pages: 924
HANDBOOK ON ARRAY PROCESSING AND SENSOR NETWORKS......Page 5
CONTENTS......Page 7
Preface......Page 15
Contributors......Page 17
Introduction......Page 21
PART I: FUNDAMENTAL ISSUES IN ARRAY SIGNAL PROCESSING......Page 29
1.1 Introduction......Page 31
1.2 Harmonizable Stochastic Processes......Page 32
1.3 Stochastic Wavefields......Page 35
1.4 Wave Dispersion......Page 39
1.5 Conclusions......Page 46
References......Page 47
2.1 Introduction......Page 49
2.2 Fundamentals......Page 53
2.3 Temporal Spectrum Estimation......Page 54
2.4 Spatial Spectrum Estimation......Page 61
References......Page 76
3.1 Introduction......Page 79
3.2 Space–Time Propagation Environment......Page 80
3.3 Propagation Models......Page 84
3.4 Measured Channel Characteristics......Page 95
3.5 Stationarity......Page 101
3.6 Summary......Page 106
References......Page 107
4.1 Introduction......Page 111
4.2 Direction-of-Arrival Estimation......Page 112
4.3 Adaptive Beamforming......Page 122
4.4 Conclusions......Page 127
References......Page 128
5.1 Introduction and Overview......Page 135
5.2 Multipath Wireless Channel Modeling in Time, Frequency, and Space......Page 138
5.3 Point-to-Point MIMO Wireless Communication Systems......Page 153
5.4 Active Wireless Sensing with Wideband MIMO Transceivers......Page 176
5.5 Concluding Remarks......Page 185
References......Page 186
PART II: NOVEL TECHNIQUES FOR AND APPLICATIONS OF ARRAY SIGNAL PROCESSING......Page 191
6.1 Introduction......Page 193
6.2 Classification of Implicit Training Methods......Page 200
6.3 IT-Based Estimation for a Single User......Page 206
6.4 IT-Based Estimation for Multiple Users Exploiting Array Processing: Continuous Transmission......Page 211
6.5 IT-Based Estimation for Multiple Users Exploiting Array Processing: Packet Transmission......Page 219
6.6 Open Research Problems......Page 221
References......Page 223
7.1 Introduction......Page 231
7.2 2 × 2 Space–Time Diversity Waveform Design......Page 233
7.3 4 × 4 Space–Time Diversity Waveform Design......Page 237
7.4 Waveform Families Based on Kronecker Products......Page 240
7.5 Introduction to Data-Dependent Waveform Design......Page 246
7.6 3 × 3 and 6 × 6 Waveform Scheduling......Page 248
References......Page 249
8.1 Introduction......Page 251
8.2 Signal Processing in Subband Domain......Page 253
8.3 Multichannel Echo Cancellation......Page 256
8.4 Speaker Localization......Page 260
8.5 Beamforming......Page 262
8.6 Sensor Calibration......Page 269
8.7 Postprocessing......Page 272
References......Page 284
9.1 Introduction......Page 289
9.2 Overview of noise reduction techniques......Page 290
9.3 Monaural beamforming......Page 292
9.4 Binaural beamforming......Page 306
References......Page 316
10.1 Introduction......Page 323
10.2 Underdetermined Blind Source Separation of Speeches in Reverberant Environments......Page 325
10.3 Sparseness of Speech Sources......Page 327
10.4 Binary Mask Approach to Underdetermined BSS......Page 332
10.5 MAP-Based Two-Stage Approach to Underdetermined BSS......Page 341
10.6 Experimental Comparison with Binary Mask Approach and MAP-Based Two-Stage Approach......Page 348
10.7 Concluding Remarks......Page 355
References......Page 357
11.2 Correlation Arrays......Page 363
11.3 Aperture Plane Phased Arrays......Page 381
11.4 Future Directions......Page 382
11.5 Conclusion......Page 384
References......Page 385
12.1 Background......Page 387
12.2 Next-Generation 3D/4D Ultrasound Imaging Technology......Page 392
12.3 Computing Architecture and Implementation Issues......Page 412
12.4 Experimental Planar Array Ultrasound Imaging System......Page 414
12.5 Conclusion......Page 423
References......Page 424
PART III: FUNDAMENTAL ISSUES IN DISTRIBUTED SENSOR NETWORKS......Page 427
13.1 Introduction......Page 429
13.2 Measurement Types and Performance Bounds......Page 431
13.3 Localization Algorithms......Page 440
13.4 Relative and Transformation Error Decomposition......Page 447
13.5 Conclusions......Page 454
References......Page 455
14.1 Introduction......Page 459
14.2 System Description and Problem Formulation......Page 460
14.3 Sequential Monte Carlo Methods......Page 466
14.4 Joint Single-Target Tracking and Classification......Page 468
14.5 Multiple-Target Tracking and Classification......Page 472
14.6 Sensor Selection......Page 476
14.7 Simulation Results......Page 479
14.8 Conclusion......Page 484
Appendix: Derivations of (14.38) and (14.40)......Page 485
References......Page 486
15.1 Introduction......Page 489
15.2 System Model......Page 491
15.3 Digital Approaches......Page 492
15.4 Analog Approaches......Page 496
15.5 Analog versus Digital......Page 505
15.6 Extension to Vector Model......Page 507
15.7 Concluding Remarks......Page 512
References......Page 514
16.1 Introduction......Page 519
16.2 Tracking Filters......Page 520
16.3 Data Association......Page 531
16.4 Out-of-Sequence Measurements......Page 541
16.5 Results with Real Data......Page 544
References......Page 547
17.1 Introduction......Page 553
17.2 Preliminaries......Page 555
17.3 Distributed Detection......Page 558
17.4 Consensus Algorithms......Page 559
17.5 Zero-Dimension (Average) Consensus......Page 562
17.6 Consensus in Higher Dimensions......Page 564
17.7 Leader–Follower (Type) Algorithms......Page 565
17.8 Localization in Sensor Networks......Page 568
17.9 Linear System of Equations: Distributed Algorithm......Page 571
References......Page 573
18.1 Introduction......Page 579
18.2 Cooperative Relay Protocols......Page 581
18.3 SER Analysis and Optimal Power Allocation......Page 588
18.4 Energy Efficiency in Cooperative Sensor Networks......Page 609
18.5 Experimental Results......Page 619
References......Page 626
19.1 Introduction......Page 629
19.2 Theoretical Background......Page 630
19.3 Code Designs......Page 639
19.4 Applications......Page 651
19.5 Conclusions......Page 658
References......Page 659
20.1 Introduction......Page 665
20.2 How Can We Implement Network Coding in a Practical Sensor Network?......Page 669
20.3 Data Collection and Coupon Collector Problem......Page 673
20.4 Distributed Storage and Sensor Network Data Persistence......Page 677
20.5 Decentralized Operation and Untuned Radios......Page 680
20.6 Broadcasting and Multipath Diversity......Page 682
20.7 Network, Channel, and Source Coding......Page 683
20.8 Identity-Aware Sensor Networks......Page 684
References......Page 686
21.1 Introduction......Page 689
21.2 Information-Theoretic Studies......Page 690
21.3 Relay Schemes......Page 694
21.4 Wireless Network Coding......Page 704
21.5 Concluding Remarks......Page 708
References......Page 709
PART IV: NOVEL TECHNIQUES FOR AND APPLICATIONS OF DISTRIBUTED SENSOR NETWORKS......Page 713
22.1 Introduction......Page 715
22.2 Motivation......Page 717
22.3 Incremental Adaptive Solutions......Page 718
22.4 Diffusion Adaptive Solutions......Page 727
22.5 Concluding Remarks......Page 740
References......Page 741
23.1 Introduction......Page 743
23.2 Spatial Data Correlation......Page 744
23.3 Statistical Inference of Markov Random Fields......Page 750
23.4 Optimal Routing for Inference with Local Processing......Page 751
23.5 Conclusion and Future Work......Page 764
References......Page 765
24 Spectral Estimation in Cognitive Radios......Page 769
24.1 Filter Bank Formulation of Spectral Estimators......Page 770
24.2 Polyphase Realization of Uniform Filter Banks......Page 771
24.3 Periodogram Spectral Estimator......Page 772
24.4 Multitaper Spectral Estimator......Page 777
24.5 Filter Bank Spectral Estimator......Page 786
24.6 Distributed Spectrum Sensing......Page 793
24.7 Discussion......Page 796
Appendix A: Effective Degree of Freedom......Page 797
References......Page 799
25.1 Introduction......Page 803
25.2 WLAN Positioning Architectures......Page 805
25.3 Signal Models......Page 806
25.4 Zero-Memory Positioning......Page 808
25.5 Dynamic Positioning Systems......Page 810
25.6 Cognition and Feedback......Page 816
25.7 Tracking Example......Page 819
References......Page 821
26.1 Introduction......Page 825
26.2 Biosensors Built of Ion Channels......Page 827
26.3 Joint Input Excitation Design and Concentration Classification for Biosensor......Page 832
26.4 Decentralized Deployment of Dense Network of Biosensors......Page 836
26.5 Discussion and Extensions......Page 846
References......Page 847
27.1 Introduction......Page 851
27.2 Physical and Statistical Models......Page 852
27.3 Transport Modeling Using Monte Carlo Approximation......Page 855
27.4 Localizing the Source(s)......Page 863
27.5 Sequential Detection......Page 866
27.6 Conclusion......Page 869
References......Page 871
28.1 Introduction......Page 875
28.2 Security and Privacy Challenges......Page 876
28.3 Ensuring Integrity of Measurement Process......Page 880
28.4 Availability Attacks against the Wireless Link......Page 888
28.5 Ensuring Privacy of Routing Contexts......Page 896
28.6 Conclusion......Page 902
References......Page 903
Index......Page 909
