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"Optimum Array Processing" by Harry L. Van Trees

"Optimum Array Processing" by Harry L. Van Trees
Detection, Estimation, and Modulation Theory, Part IV
Wilеу-Intеrsсiеnсе | 2002 | ISBN: 0471093909 9780471463832 | 1470 pages | djvu/PDF | 29/20 MB

The explanations and mathematics are crystal clear and anyone but the most indolent should have a great pleasure in the detail and effort put behind this book. This cwork covers all modern applications of array signal processing, from biomedicine to wireless communications. A great many array geometries, methods and techniques are considered and explained in detail.

1 Introduction
1.1 Array Processing
1.2 Applications
1.3 Organization of the Book
1.4 Interactive Study
2 Arrays and Spatial Filters
2.1 Introduction
2.2 Frequency-wavenumber Response and Beam Patterns
2.3 Uniform Linear Arrays
2.4 Uniformly Weighted Linear Arrays
2.4.1 Beam Pattern Parameters
2.5 Array Steering
2.6 Array Performance Measures
2.7 Linear Apertures
2.8 Non-isotropic Element Patterns
2.9 Summary
2.10 Problems
3 Synthesis of Linear Arrays and Apertures
3.1 Spectral Weighting
3.2 Array Polynomials and the z-Transform
3.3 Pattern Sampling in Wavenumber Space
3.4 Minimum Beam-width for Specified Sidelobe Level
3.5 Least Squares Error Pattern Synthesis
3.6 Minimax Design
3.7 Null Steering
3.8 Asymmetric Beams
3.9 Spatially Non-uniform Linear Arrays
3.10 Beamspace Processing
3.11 Broadband Arrays
3.12 Summary
3.13 Problems
4 Planar Arrays and Apertures
4.1 Rectangular Arrays
4.2 Circular Arrays
4.3 Circular Apertures
4.4 Hexagonal Arrays
4.5 Nonplanar Arrays
4.6 Summary 3
4.7 Problems
5 Characterization of Space-time Processes
5.1 Introduction
5.2 Snapshot Models
5.3 Space-time Random Processes
5.4 Arrays and Apertures
5.5 Orthogonal Expansions
5.6 Parametric Wavenumber Models
5.7 Summary
5.8 Problems
6 Optimum Waveform Estimation
6.1 Introduction
6.2 Optimum Beamformers
6.3 Discrete Interference
6.4 Spatially Spread Interference
6.5 Multiple Plane-wave Signals
6.6 Mismatched MVDR and MPDR Beamformers
6.7 LCMV and LCMP Beamformers
6.8 Eigenvector Beamformers
6.9 Beamspace Beamformers
6.10 Quadratically Constrained Beamformers
6.11 Soft-constraint Beamformers
6.12 Beamforming for Correlated Signal and Interferences
6.13 Broadband Beamformers
6.14 Summary
6.15 Problems
7 Adaptive Beamformers
7.1 Introduction
7.2 Estimation of Spatial Spectral Matrices
7.3 Sample Matrix Inversion (SMI)
7.4 Recursive Least Squares (RLS)
7.5 Efficient Recursive Implementation Algorithms
7.6 Gradient Algorithms
7.7 LMS Algorithms
7.8 Detection of Signal Subspace Dimension
7.9 Eigenspace and DMR Beamformers
7.10 Beamspace Beamformers
7.11 Broadband Beamformers
7.12 Summary
7.13 Problems
8 Parameter Estimation I: Maximum Likelihood
8.1 Introduction
8.2 Maximum Likelihood and Maximum a posteriori Estimators
8.3 Parameter Estimation Model
8.4 Cramer-Rao Bounds
8.5 Maximum Likelihood Estimation
8.6 Computational Algorithms
8.7 Polynomial Parameterization
8.8 Detection of Number of Signals
8.9 Spatially Spread Signals
8.10 Beamspace algorithms
8.11 Sensitivity, Robustness, and Calibration
8.12 Summary
8.13 Problems
9 Parameter Estimation II
9.1 Introduction
9.2 Quadratic Algorithms
9.3 Subspace Algorithms
9.4 Linear Prediction
9.5 Asymptotic Performance
9.6 Correlated and Coherent Signals
9.7 Beamspace Algorithms
9.8 Sensitivity and Robustness
9.9 Planar Arrays
9.10 Summary
9.11 Problems
10 Detection and Other Topics
10.1 Optimum Detection
10.2 Related Topics
10.3 Epilogue
10.4 Problems
A. Matrix Operations
A.1 Introduction
A.2 Basic Definitions and Properties
A.3 Special Vectors and Matrices
A.4 Eigensystems
A.5 Singular Value Decomposition
A.6 QR Decomposition
A.7 Derivative Operations
B. Array Processing Literature
B.1 Journals
B.2 Books
B.3 Duality
C. Notation
C.1 Conventions
C.2 Acronyms
C.3 Mathematical Symbols
C.4 Symbols


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