Sensor Array Signal Processing, Second Edition / Edition 2

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Since publication of the first edition of Sensor Array Signal Processing in 2000, the field it heralded has come of age. Sensor arrays helped usher in the age of wireless communication by meeting the increasing capacity requirements of ever growing wireless networks, but that is only one example of the number of uses served by this valuable technology across any number of fields.

Extensively updated and expanded, Sensor Array Signal Processing, Second Edition covers a wide range of interrelated topics in array processing to provide an introduction to the field that one will not find in the literature. The book introduces new developments in the use of sensors in wireless networks and the use of distributed sensors for localization. It unravels layers of complexity to explore underlying basic principles of array signal processing, focusing on the common threads that exist in wavefield analysis, rather than on particular applications.

Following an introduction to the basic equations governing different wavefields, the text provides updated coverage on current topics of interest. It analyzes various types of sensor configurations; focusing on those most useful for understanding array systems in practice — uniform linear and circular arrays.

Fully updated with over 150 new pages, this new edition:

  • Includes new chapters — emphasizing the use of sensor arrays in wireless communication and localization
  • Adds new exercises and examples to the end of each chapter
  • Provides information on emerging topics covering, distributed sensor array, multi-component sensors, space-time processing, azimuth/elevation estimation, wideband adaptive beamformation, and frequency invariant beamformation

An invaluable tool for self-study, this book provides those working in or interested in medical imaging, astronomy, radar, communications, sonar, seismology or any field that studies propagating wavefields, with a highly accessible guide. It describes each concept in precise mathematical language complete with numerical examples, detailed illustrations, and practice exercises at the end of each chapter to reinforce concepts. As with the first edition, this volume also meets the needs of professors wishing to adopt the book for graduate-level courses in telecommunications and electrical engineering.

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Product Details

  • ISBN-13: 9781420071900
  • Publisher: Taylor & Francis
  • Publication date: 6/8/2009
  • Edition number: 2
  • Pages: 556
  • Product dimensions: 6.40 (w) x 9.30 (h) x 1.40 (d)

Meet the Author

Prabhakar S. Naidu is a research consultant and retired professor from the   Indian Institute of Science, Bangalore, India. He worked at the Indian Institute of Science for nearly three decades as an assistant, associate, and full professor in the department of electrical communication engineering.  He has been awarded the NRC Fellowship (Canada 1965), Alexander von Humboldt fellowship (1979), Senior research associateship from NRC (USA), and listed in Marquis Who’s Who in the World (17th edition). He has worked as a visiting scientist at the Australian Telecommunication Research Center and has published seventy research papers and four books.
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Table of Contents

Chapter One: An Overview of Wavefields

1.1 Types of Wavefields and the Governing Equations

1.2 Wavefield in open space

1.3 Wavefield in bounded space

1.4 Stochastic wavefield

1.5 Multipath propagation

1.6 Propagation through random medium

1.7 Exercises

Chapter Two: Sensor Array Systems

2.1 Uniform linear array (ULA)

2.2 Planar array

2.3 Distributed sensor array

2.4 Broadband sensor array

2.5 Source and sensor arrays

2.6 Multi-component sensor array

2.7 Exercises

Chapter Three: Frequency Wavenumber Processing

3.1 Digital filters in the w-k domain

3.2 Mapping of 1D into 2D filters

3.3 Multichannel Wiener filters

3.4 Wiener filters for ULA and UCA

3.5 Predictive noise cancellation

3.6 Exercises

Chapter Four: Source Localization: Frequency Wavenumber Spectrum

4.1 Frequency wavenumber spectrum

4.2 Beamformation

4.3 Capon's w-k spectrum

4.4 Maximum entropy w-k spectrum

4.5 Doppler-Azimuth Processing

4.6 Exercises

Chapter Five: Source Localization: Subspace Methods

5.1 Subspace methods (Narrowband)

5.2 Subspace methods (Broadband)

5.3 Communication Signals

5.4 Array calibration

5.5 Source in Bounded Space

5.6 Azimuth/Elevation Estimation

5.7 Exercises

Chapter Six: Source Estimation

6.1 Wiener filters

6.2 Minimum variance (Capon method)

6.3 Adaptive beamformation

6.4 Wideband adaptive beamformation

6.5 Frequency Invariant Beamformation

6.6 Exercises

Chapter Seven: Multipath Channel

7.1 Overlapping Echos

7.2 Discrete Channel

7.3 Scatter Channel

7.4 Channel Estimation

7.5 Exercises

Chapter Eight: Wireless Communication

8.1 Beamformation

8.2 Multipath Communication Channel

8.3 Symbol Estimation

8.4 Exercises

Chapter Nine: Tomographic Imaging

9.1 Nondiffracting radiation

9.2 Diffracting radiation

9.3 Broadband illumination

9.4 Reflection tomography

9.5 Object shape estimation

9.6 Exercises

Chapter Ten: Imaging by Wavefield Extrapolation

10.1 Migration

10.2 Exploding reflector model

10.3 Extrapolation in w-k plane

10.4 Focused beam

10.5 Estimation of wave speed

10.6 Exercises

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