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Informationen zum Autor Prabhakar S. Naidu Klappentext Extensively updated and expanded! the second edition of this popular text covers a wide range of interrelated topics in array processing to provide an accessible introduction to the field. It reviews new developments in the use of sensors in wireless networks and in the use of distributed sensors for localization. It explores the 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! including distributed sensor array! multi-component sensors! space-time processing! azimuth/elevation estimation! wideband adaptive beamformation! and frequency invariant beamformation. Zusammenfassung Covers a range of interrelated topics in array processing to provide an introduction to the field. This book reviews developments in the use of sensors in wireless networks and in the use of distributed sensors for localization. Inhaltsverzeichnis 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 ExercisesChapter 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 array2.7 ExercisesChapter 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 Spectrum4.1 Frequency wavenumber spectrum 4.2 Beamformation 4.3 Capon's w-k spectrum 4.4 Maximum entropy w-k spectrum 4.5 Doppler-Azimuth Processing4.6 ExercisesChapter Five: Source Localization: Subspace Methods 5.1 Subspace methods (Narrowband) 5.2 Subspace methods (Broadband) 5.3 Communication Signals 5.4 Array calibration5.5 Source in Bounded Space 5.6 Azimuth/Elevation Estimation5.7 Exercises Chapter Six: Source Estimation 6.1 Wiener filters 6.2 Minimum variance (Capon method) 6.3 Adaptive beamformation 6.4 Wideband adaptive beamformation6.5 Frequency Invariant Beamformation 6.6 Exercises Chapter Seven: Multipath Channel 7.1 Overlapping Echos7.2 Discrete Channel7.3 Scatter Channel7.4 Channel Estimation7.5 Exercises Chapter Eight: Wireless Communication 8.1 Beamformation8.2 Multipath Communication Channel8.3 Symbol Estimation8.4 ExercisesChapter 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 ...
