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Handbook on Array Processing and Sensor Networks

Book Description

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.

Table of Contents

  1. Cover Page
  2. Title Page
  3. Copyright
  4. Contents
  5. Preface
  6. Contributors
  7. Introduction
    1. PART I: FUNDAMENTAL ISSUES IN ARRAY SIGNAL PROCESSING
    2. PART II: NOVEL TECHNIQUES FOR AND APPLICATIONS OF ARRAY SIGNAL PROCESSING
    3. PART III: FUNDAMENTAL ISSUES IN DISTRIBUTED SENSOR NETWORKS
    4. PART IV: NOVEL TECHNIQUES FOR AND APPLICATIONS OF DISTRIBUTED SENSOR NETWORKS
  8. PART I: FUNDAMENTAL ISSUES IN ARRAY SIGNAL PROCESSING
    1. CHAPTER 1: Wavefields
      1. 1.1 INTRODUCTION
      2. 1.2 HARMONIZABLE STOCHASTIC PROCESSES
      3. 1.3 STOCHASTIC WAVEFIELDS
      4. 1.4 WAVE DISPERSION
      5. 1.5 CONCLUSIONS
      6. ACKNOWLEDGMENTS
      7. REFERENCES
    2. CHAPTER 2: Spatial Spectrum Estimation
      1. 2.1 INTRODUCTION
      2. 2.2 FUNDAMENTALS
      3. 2.3 TEMPORAL SPECTRUM ESTIMATION
      4. 2.4 SPATIAL SPECTRUM ESTIMATION
      5. 2.5 FINAL REMARKS
      6. REFERENCES
    3. CHAPTER 3: MIMO Radio Propagation
      1. 3.1 INTRODUCTION
      2. 3.2 SPACE–TIME PROPAGATION ENVIRONMENT
      3. 3.3 PROPAGATION MODELS
      4. 3.4 MEASURED CHANNEL CHARACTERISTICS
      5. 3.5 STATIONARITY
      6. 3.6 SUMMARY
      7. REFERENCES
    4. CHAPTER 4: Robustness Issues in Sensor Array Processing
      1. 4.1 INTRODUCTION
      2. 4.2 DIRECTION-OF-ARRIVAL ESTIMATION
      3. 4.3 ADAPTIVE BEAMFORMING
      4. 4.4 CONCLUSIONS
      5. ACKNOWLEDGMENTS
      6. REFERENCES
    5. CHAPTER 5: Wireless Communication and Sensing in Multipath Environments Using Multiantenna Transceivers
      1. 5.1 INTRODUCTION AND OVERVIEW
      2. 5.2 MULTIPATH WIRELESS CHANNEL MODELING IN TIME, FREQUENCY, AND SPACE
      3. 5.3 POINT-TO-POINT MIMO WIRELESS COMMUNICATION SYSTEMS
      4. 5.4 ACTIVE WIRELESS SENSING WITH WIDEBAND MIMO TRANSCEIVERS
      5. 5.5 CONCLUDING REMARKS
      6. REFERENCES
  9. PART II: NOVEL TECHNIQUES FOR AND APPLICATIONS OF ARRAY SIGNAL PROCESSING
    1. CHAPTER 6: Implicit Training and Array Processing for Digital Communication Systems
      1. 6.1 INTRODUCTION
      2. 6.2 CLASSIFICATION OF IMPLICIT TRAINING METHODS
      3. 6.3 IT-BASED ESTIMATION FOR A SINGLE USER
      4. 6.4 IT-BASED ESTIMATION FOR MULTIPLE USERS EXPLOITING ARRAY PROCESSING: CONTINUOUS TRANSMISSION
      5. 6.5 IT-BASED ESTIMATION FOR MULTIPLE USERS EXPLOITING ARRAY PROCESSING: PACKET TRANSMISSION
      6. 6.6 OPEN RESEARCH PROBLEMS
      7. ACKNOWLEDGMENTS
      8. REFERENCES
    2. CHAPTER 7: Unitary Design of Radar Waveform Diversity Sets
      1. 7.1 INTRODUCTION
      2. 7.2 2 × 2 SPACE–TIME DIVERSITY WAVEFORM DESIGN
      3. 7.3 4 × 4 SPACE–TIME DIVERSITY WAVEFORM DESIGN
      4. 7.4 WAVEFORM FAMILIES BASED ON KRONECKER PRODUCTS
      5. 7.5 INTRODUCTION TO DATA-DEPENDENT WAVEFORM DESIGN
      6. 7.6 3 × 3 AND 6 × 6 WAVEFORM SCHEDULING
      7. 7.7 SUMMARY
      8. REFERENCES
    3. CHAPTER 8: Acoustic Array Processing for Speech Enhancement
      1. 8.1 INTRODUCTION
      2. 8.2 SIGNAL PROCESSING IN SUBBAND DOMAIN
      3. 8.3 MULTICHANNEL ECHO CANCELLATION
      4. 8.4 SPEAKER LOCALIZATION
      5. 8.5 BEAMFORMING
      6. 8.6 SENSOR CALIBRATION
      7. 8.7 POSTPROCESSING
      8. 8.8 CONCLUSIONS
      9. REFERENCES
    4. CHAPTER 9: Acoustic Beamforming for Hearing Aid Applications
      1. 9.1 INTRODUCTION
      2. 9.2 OVERVIEW OF NOISE REDUCTION TECHNIQUES
      3. 9.3 MONAURAL BEAMFORMING
      4. 9.4 BINAURAL BEAMFORMING
      5. 9.5 CONCLUSION
      6. REFERENCES
    5. CHAPTER 10: Underdetermined Blind Source Separation Using Acoustic Arrays
      1. 10.1 INTRODUCTION
      2. 10.2 UNDERDETERMINED BLIND SOURCE SEPARATION OF SPEECHES IN REVERBERANT ENVIRONMENTS
      3. 10.3 SPARSENESS OF SPEECH SOURCES
      4. 10.4 BINARY MASK APPROACH TO UNDERDETERMINED BSS
      5. 10.5 MAP-BASED TWO-STAGE APPROACH TO UNDERDETERMINED BSS
      6. 10.6 EXPERIMENTAL COMPARISON WITH BINARY MASK APPROACH AND MAP-BASED TWO-STAGE APPROACH
      7. 10.7 CONCLUDING REMARKS
      8. REFERENCES
    6. CHAPTER 11: Array Processing in Astronomy
      1. 11.1 INTRODUCTION
      2. 11.2 CORRELATION ARRAYS
      3. 11.3 APERTURE PLANE PHASED ARRAYS
      4. 11.4 FUTURE DIRECTIONS
      5. 11.5 CONCLUSION
      6. REFERENCES
    7. CHAPTER 12: Digital 3D/4D Ultrasound Imaging Array
      1. 12.1 BACKGROUND
      2. 12.2 NEXT-GENERATION 3D/4D ULTRASOUND IMAGING TECHNOLOGY
      3. 12.3 COMPUTING ARCHITECTURE AND IMPLEMENTATION ISSUES
      4. 12.4 EXPERIMENTAL PLANAR ARRAY ULTRASOUND IMAGING SYSTEM
      5. 12.5 CONCLUSION
      6. REFERENCES
  10. PART III: FUNDAMENTAL ISSUES IN DISTRIBUTED SENSOR NETWORKS
    1. CHAPTER 13: Self-Localization of Sensor Networks
      1. 13.1 INTRODUCTION
      2. 13.2 MEASUREMENT TYPES AND PERFORMANCE BOUNDS
      3. 13.3 LOCALIZATION ALGORITHMS
      4. 13.4 RELATIVE AND TRANSFORMATION ERROR DECOMPOSITION
      5. 13.5 CONCLUSIONS
      6. REFERENCES
    2. CHAPTER 14: Multitarget Tracking and Classification in Collaborative Sensor Networks via Sequential Monte Carlo Methods
      1. 14.1 INTRODUCTION
      2. 14.2 SYSTEM DESCRIPTION AND PROBLEM FORMULATION
      3. 14.3 SEQUENTIAL MONTE CARLO METHODS
      4. 14.4 JOINT SINGLE-TARGET TRACKING AND CLASSIFICATION
      5. 14.5 MULTIPLE-TARGET TRACKING AND CLASSIFICATION
      6. 14.6 SENSOR SELECTION
      7. 14.7 SIMULATION RESULTS
      8. 14.8 CONCLUSION
      9. APPENDIX: DERIVATIONS OF ( 14.38 ) AND ( 14.40 )
      10. REFERENCES
    3. CHAPTER 15: Energy-Efficient Decentralized Estimation
      1. 15.1 INTRODUCTION
      2. 15.2 SYSTEM MODEL
      3. 15.3 DIGITAL APPROACHES
      4. 15.4 ANALOG APPROACHES
      5. 15.5 ANALOG VERSUS DIGITAL
      6. 15.6 EXTENSION TO VECTOR MODEL
      7. 15.7 CONCLUDING REMARKS
      8. ACKNOWLEDGMENTS
      9. REFERENCES
    4. CHAPTER 16: Sensor Data Fusion with Application to Multitarget Tracking
      1. 16.1 INTRODUCTION
      2. 16.2 TRACKING FILTERS
      3. 16.3 DATA ASSOCIATION
      4. 16.4 OUT-OF-SEQUENCE MEASUREMENTS
      5. 16.5 RESULTS WITH REAL DATA [58]
      6. 16.6 SUMMARY
      7. REFERENCES
    5. CHAPTER 17: Distributed Algorithms in Sensor Networks
      1. 17.1 INTRODUCTION
      2. 17.2 PRELIMINARIES
      3. 17.3 DISTRIBUTED DETECTION
      4. 17.4 CONSENSUS ALGORITHMS
      5. 17.5 ZERO-DIMENSION (AVERAGE) CONSENSUS
      6. 17.6 CONSENSUS IN HIGHER DIMENSIONS
      7. 17.7 LEADER–FOLLOWER (TYPE) ALGORITHMS
      8. 17.8 LOCALIZATION IN SENSOR NETWORKS
      9. 17.9 LINEAR SYSTEM OF EQUATIONS: DISTRIBUTED ALGORITHM
      10. 17.10 CONCLUSIONS
      11. REFERENCES
    6. CHAPTER 18: Cooperative Sensor Communications
      1. 18.1 INTRODUCTION
      2. 18.2 COOPERATIVE RELAY PROTOCOLS
      3. 18.3 SER ANALYSIS AND OPTIMAL POWER ALLOCATION
      4. 18.4 ENERGY EFFICIENCY IN COOPERATIVE SENSOR NETWORKS
      5. 18.5 EXPERIMENTAL RESULTS
      6. 18.6 CONCLUSIONS
      7. REFERENCES
    7. CHAPTER 19: Distributed Source Coding
      1. 19.1 INTRODUCTION
      2. 19.2 THEORETICAL BACKGROUND
      3. 19.3 CODE DESIGNS
      4. 19.4 APPLICATIONS
      5. 19.5 CONCLUSIONS
      6. REFERENCES
    8. CHAPTER 20: Network Coding for Sensor Networks
      1. 20.1 INTRODUCTION
      2. 20.2 HOW CAN WE IMPLEMENT NETWORK CODING IN A PRACTICAL SENSOR NETWORK?
      3. 20.3 DATA COLLECTION AND COUPON COLLECTOR PROBLEM
      4. 20.4 DISTRIBUTED STORAGE AND SENSOR NETWORK DATA PERSISTENCE
      5. 20.5 DECENTRALIZED OPERATION AND UNTUNED RADIOS
      6. 20.6 BROADCASTING AND MULTIPATH DIVERSITY
      7. 20.7 NETWORK, CHANNEL, AND SOURCE CODING
      8. 20.8 IDENTITY-AWARE SENSOR NETWORKS
      9. 20.9 DISCUSSION
      10. ACKNOWLEDGMENTS
      11. REFERENCES
    9. CHAPTER 21: Information-Theoretic Studies of Wireless Sensor Networks
      1. 21.1 INTRODUCTION
      2. 21.2 INFORMATION-THEORETIC STUDIES
      3. 21.3 RELAY SCHEMES
      4. 21.4 WIRELESS NETWORK CODING
      5. 21.5 CONCLUDING REMARKS
      6. ACKNOWLEDGMENTS
      7. REFERENCES
  11. PART IV: Novel Techniques for and Applications of Distributed Sensor Networks
    1. CHAPTER 22: Distributed Adaptive Learning Mechanisms
      1. 22.1 INTRODUCTION
      2. 22.2 MOTIVATION
      3. 22.3 INCREMENTAL ADAPTIVE SOLUTIONS
      4. 22.4 DIFFUSION ADAPTIVE SOLUTIONS
      5. 22.5 CONCLUDING REMARKS
      6. ACKNOWLEDGMENTS
      7. REFERENCES
    2. CHAPTER 23: Routing for Statistical Inference in Sensor Networks
      1. 23.1 INTRODUCTION
      2. 23.2 SPATIAL DATA CORRELATION
      3. 23.3 STATISTICAL INFERENCE OF MARKOV RANDOM FIELDS
      4. 23.4 OPTIMAL ROUTING FOR INFERENCE WITH LOCAL PROCESSING
      5. 23.5 CONCLUSION AND FUTURE WORK
      6. 23.6 BIBLIOGRAPHIC NOTES
      7. REFERENCES
    3. CHAPTER 24: Spectral Estimation in Cognitive Radios
      1. 24.1 FILTER BANK FORMULATION OF SPECTRAL ESTIMATORS
      2. 24.2 POLYPHASE REALIZATION OF UNIFORM FILTER BANKS
      3. 24.3 PERIODOGRAM SPECTRAL ESTIMATOR
      4. 24.4 MULTITAPER SPECTRAL ESTIMATOR
      5. 24.5 FILTER BANK SPECTRAL ESTIMATOR
      6. 24.6 DISTRIBUTED SPECTRUM SENSING
      7. 24.7 DISCUSSION
      8. APPENDIX A: EFFECTIVE DEGREE OF FREEDOM
      9. APPENDIX B: EXPLANATION TO THE RESULTS OF Table 24.1
      10. REFERENCES
    4. CHAPTER 25: Nonparametric Techniques for Pedestrian Tracking in Wireless Local Area Networks
      1. 25.1 INTRODUCTION
      2. 25.2 WLAN POSITIONING ARCHITECTURES
      3. 25.3 SIGNAL MODELS
      4. 25.4 ZERO-MEMORY POSITIONING
      5. 25.5 DYNAMIC POSITIONING SYSTEMS
      6. 25.6 COGNITION AND FEEDBACK
      7. 25.7 TRACKING EXAMPLE
      8. 25.8 CONCLUSIONS
      9. REFERENCES
    5. CHAPTER 26: Reconfigurable Self-Activating Ion-Channel-Based Biosensors
      1. 26.1 INTRODUCTION
      2. 26.2 BIOSENSORS BUILT OF ION CHANNELS
      3. 26.3 JOINT INPUT EXCITATION DESIGN AND CONCENTRATION CLASSIFICATION FOR BIOSENSOR
      4. 26.4 DECENTRALIZED DEPLOYMENT OF DENSE NETWORK OF BIOSENSORS
      5. 26.5 DISCUSSION AND EXTENSIONS
      6. REFERENCES
    6. CHAPTER 27: Biochemical Transport Modeling, Estimation, and Detection in Realistic Environments
      1. 27.1 INTRODUCTION
      2. 27.2 PHYSICAL AND STATISTICAL MODELS
      3. 27.3 TRANSPORT MODELING USING MONTE CARLO APPROXIMATION
      4. 27.4 LOCALIZING THE SOURCE(S)
      5. 27.5 SEQUENTIAL DETECTION
      6. 27.6 CONCLUSION
      7. REFERENCES
    7. CHAPTER 28: Security and Privacy for Sensor Networks
      1. 28.1 INTRODUCTION
      2. 28.2 SECURITY AND PRIVACY CHALLENGES
      3. 28.3 ENSURING INTEGRITY OF MEASUREMENT PROCESS
      4. 28.4 AVAILABILITY ATTACKS AGAINST THE WIRELESS LINK
      5. 28.5 ENSURING PRIVACY OF ROUTING CONTEXTS
      6. 28.6 CONCLUSION
      7. REFERENCES
  12. INDEX