Haykin S., Liu K.J.R. Handbook on Array Processing and Sensor Networks

IEEE/John Wiley, 2009, -924 p.More than a decade ago, a book edited by Simon Haykin on array processing was a huge success with significant impact. Ever since, the field of array processing has grown to the extent that one can see its applications everywhere. Indeed, traditional array techniques form the foundation of the more general sensor processing and networking that continue to advance the state-of-the-art research and find ubiquitous applications. Sensor networks and array processing form the two pillars of the proposed handbook. Sensors and array processing, in their own individual ways, have been active areas of research for several decades: Wireless communications, radar, radio astronomy, and biomedical engineering, just to name a few important ones. This new Handbook on Array Processing and Sensor Networks addresses these topics in an organized manner under a single umbrella.
The major goal of this Handbook is to collect tutorial discussions on recent advancements and state-of-the-art results by providing a comprehensive overview of array processing and sensor networks. It covers fundamental principles as well as applications.
This handbook features some of the most prominent researchers from all over the world, addressing the important topics that we consider to be essential for making the handbook highly valuable to the readers; this point is well borne out by the list of contents.
This Handbook consists of an introductory chapter, followed by 28 chapters that are written by leading authorities in sensor networks and array signal processing. Putting all this material together under a single umbrella, we have a Handbook that is one of a kind.
This Handbook should appeal to researchers as well as graduate students and newcomers to the field of sensors and array processing, and thereby learn not only about the many facets of these two subjects but also exploit the possibility of cross fertilization between them. Moreover, this Handbook may also appeal to professors in teaching graduate courses on sensor networks and/or array signal processing.
Part I: Fundamental Issues in Array Signal Processing.
Wavefields.
Spatial Spectrum Estimation.
MIMO Radio Propagation.
Robustness Issues in Sensor Array Processing.
Wireless Communication and Sensing in Multipath Environments Using Multiantenna Transceivers.
Part II: Novel Techniques for and Applications of Array Signal Processing.
Implicit Training and Array Processing for Digital Communication Systems.
Unitary Design of Radar Waveform Diversity Sets.
Acoustic Array Processing for Speech Enhancement.
Acoustic Beamforming for Hearing Aid Applications.
Underdetermined Blind Source Separation Using Acoustic Arrays.
Array Processing in Astronomy.
Digital 3D/4D Ultrasound Imaging Array.
Part III: Fundamental Issues in Distributed Sensor Networks.
Self-Localization of Sensor Networks.
Multitarget Tracking and Classification in Collaborative Sensor Networks via Sequential Monte Carlo Methods.
Energy-Efficient Decentralized Estimation.
Sensor Data Fusion with Application to Multitarget Tracking.
Distributed Algorithms in Sensor Networks.
Cooperative Sensor Communications.
Distributed Source Coding.
Network Coding for Sensor Networks.
Information-Theoretic Studies of Wireless Sensor Networks.
Part IV: Novel Techniques for and Applications of Distributed Sensor Networks.
Distributed Adaptive Learning Mechanisms.
Routing for Statistical Inference in Sensor Networks.
Spectral Estimation in Cognitive Radios.
Nonparametric Techniques for Pedestrian Tracking in Wireless Local Area Networks.
Reconfigurable Self-Activating Ion-Channel-Based Biosensors.
Biochemical Transport Modeling, Estimation, and Detection in Realistic Environments.
Security and Privacy for Sensor Networks.