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
Biography
Prabhakar S. Naidu
