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Summary Table of Contents Author Biography

Handbook on Array Processing and Sensor NetworksSimon Haykin & K. J. Ray LiuA handbook on recent advancements and the state of the art in array processing and sensor NetworksHandbook 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; ... MOREMIMO 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.

The field of array processing has grown to the extent that one can see its applications everywhere, ranging from military radar/sonar to wireless communications. Featuring contributions by world-renowned experts in their fields, Handbook on Sensor and Array Processing collects tutorial articles on recent advancements and state-of-the-art results by providing a comprehensive overview of sensor and array processing. This first published book on the subject covers fundamental principles as well as applications, making it a must have for researchers, professors, graduate students, and practitioners.

A collection of tutorial articles on recent advancements and state-of-the-art results Provides a comprehensive overview of sensor and array processing. Covers fundamental principles as well as applications.

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.

Preface
Wavefields
Introduction
Harmonizable Stochastic Processes
Stochastic Wavefields
Wave Dispersion
Conclusions
Acknowledgements
Spatial Spectrum Estimation
Introduction
Fundamentals
Temporal spectrum estimation
Non-par... MOREametric methods
Spatial spectrum estimation
The model
Non-parametric methods
Parametric methods
Estimation of the number of impinging signals
Final remarks
MIMO Radio Propagation
Introduction
The space-time propagation environment
Propagation models
Measured channel characteristics
Stationarity

Robustness Issues in Sensor Array Processing
Robustness Issues in Sensor Array Processing
Direction-of-arrival estimation
Adaptive beamforming
Conclusions
Wireless Communication and Sensing in Multipath Environments Using Multi Antenna Transceivers
Overview
Multipath Wireless Channel Modeling in Time, Frequency and Space
MIMO Wireless Communication Systems
Active Wireless Sensing
Directions for Future Research
Concluding Remarks
Implicit Training and Array Processing for Digital Communications Systems
Introduction
Classification of Implicit Training Methods
IT-Based Estimation for a Single User
IT-Based Estimation for Multiple Users Exploiting Array Processing: Continuous Transmission
IT-Based Estimation for Multiple Users Exploiting Array Processing: Packet Transmission
Open Research Problems
References
Unitary Design of Radar Waveform Diversity Sets
Introduction
2x2 Space-Time Diversity Waveform Design
4x4 Space-Time Diversity Waveform Design
Waveform Families Based on Kronecker Products
Introduction to Data Dependent Waveform Design
3x3 and 6x6 Waveform Scheduling
Summary
Acoustic Array Processing for Speech Enhancement
Introduction
Signal Processing in the Subband Domain
Multi-Channel Echo Cancelation
Speaker Localization
Beamforming
Sensor Calibration
Postprocessing
Conclusions
References
Acoustic Beamforming for Hearing Aid Applications
Introduction
Overview of Noise Reduction Techniques
Monaural Beamforming
Binaural Beamforming
Conclusion
Undetermined Blind Source Separation using Acoustic Arrays
Introduction
Underdetermined Blind Source Separation of Speeches in Reverberant Environments
Sparseness of Speech Sources
Binary Mask Approach to Underdetermined BSS
MAP-Based Two-Stage Approach to Underdetermined BSS
Experimental Comparison with Binary Mask Approach and MAP-Based Two-Stage Approach
Concluding Remarks
References
Index
Array Processing in Astronomy (Douglas C.-JBock)
Introduction
Correlation Arrays
Aperture Plane Phased Arrays
Future Directions
Conclusion
Digital 3D/4D Ultrasound Imaging Technology
Background
Next Generation 3D/4D Ultrasound Imaging Technology
Computing Architecture and Implementation Issues
An Experimental Planar Array Ultrasound Imaging System
Conclusion
Reference
Self-Localization of Sensor Networks
Introduction
The Self-localization Problem
Algorithm Classifications

Localization Algorithms
Relative and Transformation Error Decomposition
Conclusions
Multi-Target Tracking and Classification in Collaborative Sensor Networks via Sequential Monte Carlo
Introduction
System Description and Problem Formulation
Sequential Monte Carlo (SMC) Methods
Joint Single Target Tracking And Classification
Multiple Target Tracking and Classification
Sensor Selection
Simulation Results
Conclusion
Energy-Efficient Decentralized Estimation
Motivation and Introduction
Distributed Estimation: Digital Approaches
Distributed Estimation: Analog Approaches
Distributed Anti-jammer Sensing via Game Theory
Future research discussion
Sensor Data Fusion with Application to Multi-Target Tracking
Introduction
Tracking Filters
Data Association
Out-of-Sequence Measurements
Results with Real Data
Distributed Algorithms in Sensor Networks
Introduction
Preliminaries
Distributed Detection
Consensus Algorithms
Zero-Dimension (Average) Consensus
Consensus in Higher Dimensions
Leader-Follower (type) Algorithms
Localization in Sensor Networks
Linear System of Equations: Distributed Algorithm
Conclusions
Cooperative Sensor Communications
Introduction
Cooperative Relay Protocols
Performance Analysis and Optimal Power Allocation
Energy Efficiency in Cooperative Sensor Networks
Experimental Results
Conclusions
Distributed Source Coding
Introduction
Theoretical background
Code designs
Applications
Conclusions
Network Coding for Sensor Networks
I Introduction
II How can we implement network coding in a practical sensor network
III Data collection and the coupon collectors problem
IV Distributed storage and sensor network data persistence
V Decentralized operation and untuned radios
VI Broadcasting and multipath diversity
VII Network, channel and source coding
VIII Identity aware sensor networks
IX Discussion
Information-Theoretic Studies of Wireless Sensor Networks
Information-Theoretic Studies of Wireless Sensor Networks
Information-theoretic studies
Relay schemes
Wireless network coding
Concluding remarks
Distributed Adaptive Learning Mechanisms
Introduction
Motivation
Incremental Adaptive Solutions
Diffusion Adaptive Solutions
Concluding Remarks
References
Routing for Statistical Inference in Sensor Networks
Introduction
Spatial Data Correlation
Statistical Inference of Markov Random Fields
Optimal Routing for Inference with Local Processing
Conclusion and Future Work 2
Spectrum Estimation in Cognitive Radios
I Filter Bank Formulation of Spectral Estimators
II Polyphase Realization of Uniform Filter Banks
III Periodogram Spectral Estimator
IV Multitaper Spectral Estimator
V Filter Bank Spectral Estimator
VI Distributed Spectrum Sensing
VII Discussion
Nonparametric Techniques for Pedestrian Tracking in Wireless Local Area Networks
Introduction
WLAN Positioning Architectures
Signal Models
Zero-Memory Positioning
Dynamic Positioning Systems
Cognition & Feedback
Tracking Example
Conclusions
References
Reconfigurable Self-Activating Ion-Channel Based Biosensors: Signal Processing and Networking via the Theory of Global Games
Introduction
Biosensors built of ion channels
Joint Input Excitation and Concentration Classification of Biosensor
Decentralized Deployment of Dense Network of Biosensors
Discussion and Extensions
Biochemical Transport Modeling, Estimation and Detection in Realistic Environments
Introduction
Physical, statistical and numerical models
Localizing the sources
Sequential Detection
Conclusion
Security and Privacy for Sensor Networks
Introduction2
Security and Privacy Challenges
Ensuring the Integrity of the Measurement Process
Availability Attacks against the Wireless Link
Ensuring Privacy of Routing Contexts
Conclusion
Table of Contents provided by Publisher. All Rights Reserved.

Simon Haykin, PhD,?is a Distinguished University Professor at McMaster University, Hamilton, Ontario. K. J. Ray Liu is a Distinguished Scholar-Teacher at the University of Maryland, College Park. He is the recipient of numerous honors and awards including best paper awards from IEEE Signal Processing Society, IEEE Vehicular Technology Society, and EURASIP, as well as recognition from the University of Maryland, including Invention of the Year Award, Poole and Kent Senior Faculty Teaching Award, and Outstanding Faculty Research Award. Dr. Liu is a Fellow of the IEEE and AAAS.

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