Array Signal Processing

Overview

This monograph is intended as an introduction to array signal processing. Array processing is a key feature of sonar, radar, and seismic signal processing. The primary emphasis here is to focus on the detection problem and the estimation problem from a signal processing viewpoint. The book can be used borh as a graduate textbook and as a reference book for engineers and researchers.

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Paperback (Softcover reprint of the original 1st ed. 1989)
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Overview

This monograph is intended as an introduction to array signal processing. Array processing is a key feature of sonar, radar, and seismic signal processing. The primary emphasis here is to focus on the detection problem and the estimation problem from a signal processing viewpoint. The book can be used borh as a graduate textbook and as a reference book for engineers and researchers.

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Editorial Reviews

Booknews
Graduate textbook and reference for engineers and researchers withg a background in basic probability theory and stochastic processes. Introduces array signal processing where the principal objective is to use the multiople sensor information to detect and estimate the signals and their parameters present in the scene. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

  • ISBN-13: 9781461281863
  • Publisher: Springer New York
  • Publication date: 7/31/2012
  • Series: Signal Processing and Digital Filtering Series
  • Edition description: Softcover reprint of the original 1st ed. 1989
  • Edition number: 1
  • Pages: 221
  • Product dimensions: 6.14 (w) x 9.21 (h) x 0.50 (d)

Table of Contents

1 Introduction.- 1.1 Introduction.- 1.2 Organization of the Book.- 1.3 Notations and Preliminaries.- 2 Detection of Multiple Signals.- 2.1 Signals and Noise.- 2.2 Conventional Techniques.- 2.2.1 Beamformer.- 2.2.2 Capon’s Minimum Variance Estimator.- 2.2.3 Linear Prediction Method.- 2.3 Eigenvector-Based Techniques.- 2.3.1 Completely Coherent Case.- 2.3.2 Symmetric Array Scheme: Coherent Sources in a Correlated Scene.- 2.3.3 Spatial Smoothing Schemes: Direction Finding in a Coherent Environment.- 2.4 Augmentation and Other Techniques.- 2.4.1 Augmentation Technique.- 2.4.2 ESPRIT, TLS-ESPRIT and GEESE.- 2.4.3 Direction Finding Using First Order Statistics.- Appendix 2.A Coherent and Correlated Signal Scene.- Appendix 2.B Program Listings.- Problems.- References.- 3 Performance Analysis.- 3.1 Introduction.- 3.2 The Maximum Likelihood Estimate of the Covariance Matrix and Some Related Distributions.- 3.3 Performance Analysis of Covariance Based Eigenvector Techniques: MUSIC and Spatial Smoothing Schemes.- 3.3.1 Asymptotic Distribution of Eigenparameters Associated with Smoothed Sample Covariance Matrices.- 3.3.2 Two-Source Case — Uncorrelated and Coherent Scene.- 3.4 Performance Evaluation of GEESE Scheme.- 3.4.1 The Least Favorable Configuration (J = K).- 3.4.2 The Most Favorable Configuration (J = M - 1).- 3.5 Estimation of Number of Signals.- Appendix 3.A The Complex Wishart Distribution.- Appendix 3.B Equivalence of Eigenvectors.- Appendix 3.C Eigenparameters in a Two Source Case.- Problems.- References.- 4 Estimation of Multiple Signals.- 4.1 Introduction.- 4.2 Optimum Processing: Steady State Performance and the Wiener Solution.- 4.3 Implementation of the Wiener Solution.- 4.3.1 The Method of Steepest Descent.- 4.3.2 The Least Mean Square (LMS) Algorithm.- 4.3.3 Direct Implementation by Inversion of the Sample Covariance Matrix.- Problems.- References.

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