Signal processing plays an important role in many diverse application areas, including radar, sonar, communications, seismology, radio astronomy, tomography, and communications. Now, by popular demand, acclaimed author Harry Van Trees' four-part encyclopedic treatment of signal processing is now collected into a set offering 25 years of information in a single source.

Well-known authority, Dr. Van Trees updates array signal processing for today's technology This is the most up-to-date and thorough treatment of the subject available Written in the same accessible style as Van Tree's earlier classics, this completely new work covers all modern applications of array signal processing, from biomedicine to wireless communications

Well-known authority, Dr. Van Trees updates array signalprocessing for today's technology This is the most up-to-date and thorough treatment of thesubject available Written in the same accessible style as Van Tree's earlierclassics, this completely new work covers all modern applicationsof array signal processing, from biomedicine to wirelesscommunications

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.

This book provides a comprehensive introduction to the theory and practice of spherical microphone arrays, and was written for graduate students, researchers and engineers who work with spherical microphone arrays in a wide range of applications. The new edition includes additions and modifications, and references supplementary Matlab code to provide the reader with a straightforward start for own implementations. The book is also accompanied by a Matlab manual, which explains how to implement the examples and simulations presented in the book. The first two chapters provide the reader with the necessary mathematical and physical background, including an introduction to the spherical Fourier transform and the formulation of plane-wave sound fields in the spherical harmonic domain. In turn, the third chapter covers the theory of spatial sampling, employed when selecting the positions of microphones to sample sound pressure functions in space. Subsequent chapters highlight various spherical array configurations, including the popular rigid-sphere-based configuration. Beamforming (spatial filtering) in the spherical harmonics domain, including axis-symmetric beamforming, and the performance measures of directivity index and white noise gain are introduced, and a range of optimal beamformers for spherical arrays, including those that achieve maximum directivity and maximum robustness are developed, along with the Dolph–Chebyshev beamformer. The final chapter discusses more advanced beamformers, such as MVDR (minimum variance distortionless response) and LCMV (linearly constrained minimum variance) types, which are tailored to the measured sound field. Mathworks kindly distributes the Matlab sources for this book on https://www.mathworks.com/matlabcentral/fileexchange/68655-fundamentals-of-spherical-array-processing.

Introduction to Adaptive Arrays serves as an introduction to the subject of adaptive sensor systems whose principle purpose is to enhance the detection and reception of certain desired signals. The field of array sensor systems is now a maturing technology. With applications of these systems growing more and more numerous, there is a wealth of widely scattered literature on various aspects of such systems. Unfortunately, few books attempt to provide an integrated treatment of the entire system that gives the reader the perspective to organize the available literature into easily understood parts. Intended for use both as a graduate level textbook and as a reference work for engineers, scientists, and systems analysts, this book provides such an integrated treatment by emphasizing the principles and techniques that are of fundamental importance in modern adaptive array systems.

Radar Array Processing presents modern techniques and methods for processingradar signals received by an array of antenna elements. With the recent rapid growth of the technology of hardware for digital signal processing, itis now possible to apply this to radar signals and thus to enlist the full power of sophisticated computational algorithms. Topics covered in detail here include: super-resolution methods of array signal processing as applied to radar, adaptive beam forming for radar, and radar imaging. This book will be of interest to researchers and studentsin the radar community and also in related fields such as sonar, seismology, acoustics and radio astronomy.