Robust Adaptive Beamforming,9780471678502

Robust Adaptive Beamforming

by ;
Edition: 1st
ISBN13: 9780471678502
ISBN10: 0471678503
Format: Hardcover
Pub. Date: 2005-10-05
Publisher(s): Wiley-Interscience
List Price: $222.87

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Summary

The latest research and developments in robust adaptive beamforming Recent work has made great strides toward devising robust adaptive beamformers that vastly improve signal strength against background noise and directional interference. This dynamic technology has diverse applications, including radar, sonar, acoustics, astronomy, seismology, communications, and medical imaging. There are also exciting emerging applications such as smart antennas for wireless communications, handheld ultrasound imaging systems, and directional hearing aids. Robust Adaptive Beamforming compiles the theories and work of leading researchers investigating various approaches in one comprehensive volume. Unlike previous efforts, these pioneering studies are based on theories that use an uncertainty set of the array steering vector. The researchers define their theories, explain their methodologies, and present their conclusions. Methods presented include: * Coupling the standard Capon beamformers with a spherical or ellipsoidal uncertainty set of the array steering vector * Diagonal loading for finite sample size beamforming * Mean-squared error beamforming for signal estimation * Constant modulus beamforming * Robust wideband beamforming using a steered adaptive beamformer to adapt the weight vector within a generalized sidelobe canceller formulation Robust Adaptive Beamforming provides a truly up-to-date resource and reference for engineers, researchers, and graduate students in this promising, rapidly expanding field.

Author Biography

JIAN LI, PhD, is Professor and Director of the Spectral Analysis Laboratory of the Department of Electrical and Computer Engineering at the University of Florida. She has coedited one book, coauthored one book and two book chapters, and published approximately 250 refereed technical conference contributions and journal papers, many of which are on topics related to array signal processing.

PETRE STOICA, PhD, is Professor of System Modeling in the Department of Systems and Control at Uppsala University, Sweden. He has coedited two books, coauthored nine books, and published approximately 500 refereed technical conference contributions and journal papers, many of which are on topics related to array signal processing.

Table of Contents

Contributors ix
Preface xi
Robust Minimum Variance Beamforming
1(48)
Robert G. Lorenz
Stephen P. Boyd
Introduction
1(7)
A Practical Example
8(4)
Robust Weight Selection
12(11)
A Numerical Example
23(5)
Ellipsoidal Modeling
28(3)
Uncertainty Ellipsoid Calculus
31(10)
Beamforming Example with Multiplicative Uncertainties
41(3)
Summary
44(5)
Appendix: Notation and Glossary
44(1)
References
45(4)
Robust Adaptive Beamforming Based on Worst-Case Performance Optimization
49(42)
Alex B. Gershman
Zhi-Quan Luo
Shahram Shahbazpanahi
Introduction
49(2)
Background and Traditional Approaches
51(9)
Robust Minimum Variance Beamforming Based on Worst-Case Performance Optimization
60(14)
Numerical Examples
74(6)
Conclusions
80(11)
Appendix 2.A: Proof of Lemma 1
81(1)
Appendix 2.B: Proof of Lemma 2
81(1)
Appendix 2.C: Proof of Lemma 3
82(2)
Appendix 2.D: Proof of Lemma 4
84(1)
Appendix 2.E: Proof of Lemma 5
85(1)
References
85(6)
Robust Capon Beamforming
91(110)
Jian Li
Petre Stoica
Zhisong Wang
Introduction
91(2)
Problem Formulation
93(2)
Standard Capon Beamforming
95(1)
Robust Capon Beamforming with Single Constraint
96(16)
Capon Beamforming with Norm Constraint
112(4)
Robust Capon Beamforming with Double Constraints
116(17)
Robust Capon Beamforming with Constant Beamwidth and Constant Powerwidth
133(15)
Rank-Deficient Robust Capon Filter-Bank Spectral Estimator
148(18)
Adaptive Imaging for Forward-Looking Ground Penetrating Radar
166(19)
Summary
185(16)
Acknowledgments
185(1)
Appendix 3.A: Relationship between RCB and the Approach in [14]
185(3)
Appendix 3.B: Calculating the Steering Vector
188(1)
Appendix 3.C: Relationship between RCB and the Approach in [15]
189(1)
Appendix 3.D: Analysis of Equation (3.72)
190(1)
Appendix 3.E: Rank-Deficient Capon Beamformer
191(2)
Appendix 3.F: Conjugate Symmetry of the Forward-Backward FIR
193(1)
Appendix 3.G: Formulations of NCCF and HDI
194(1)
Appendix 3.H: Notations and Abbreviations
195(1)
References
196(5)
Diagonal Loading for Finite Sample Size Beamforming: An Asymptotic Approach
201(58)
Xavier Mestre
Miguel A. Lagunas
Introduction and Historical Review
202(11)
Asymptotic Output SINR with Diagonal Loading
213(12)
Estimating the Asymptotically Optimum Loading Factor
225(11)
Characterization of the Asymptotically Optimum Loading Factor
236(7)
Summary and Conclusions
243(16)
Acknowledgments
243(1)
Appendix 4.A: Proof of Proposition 1
243(3)
Appendix 4.B: Proof of Lemma 1
246(1)
Appendix 4.C: Derivation of the Consistent Estimator
247(2)
Appendix 4.D: Proof of Proposition 2
249(5)
References
254(5)
Mean-Squared Error Beamforming for Signal Estimation: A Competitive Approach
259(40)
Yonina C. Eldar
Arye Nehorai
Introduction
259(2)
Background and Problem Formulation
261(10)
Minimax MSE Beamforming for Known Steering Vector
271(10)
Random Steering Vector
281(3)
Practical Considerations
284(1)
Numerical Examples
285(9)
Summary
294(5)
Acknowledgments
295(1)
References
296(3)
Constant Modulus Beamforming
299(54)
Alle-Jan van der Veen
Amir Leshem
Introduction
299(4)
The Constant Modulus Algorithm
303(4)
Prewhitening and Rank Reduction
307(5)
Multiuser CMA Techniques
312(3)
The Analytical CMA
315(10)
Adaptive Prewhitening
325(3)
Adaptive ACMA
328(10)
DOA Assisted Beamforming of Constant Modulus Signals
338(9)
Concluding Remarks
347(6)
Acknowledgment
347(1)
References
347(6)
Robust Wideband Beamforming
353(64)
Elio D. Di Claudio
Raffaele Parisi
Introduction
353(4)
Notation
357(1)
Wideband Array Signal Model
358(5)
Wideband Beamforming
363(6)
Robustness
369(12)
Steered Adaptive Beamforming
381(8)
Maximum Likelihood STBF
389(4)
ML-STBF Optimization
393(6)
Special Topics
399(2)
Experiments
401(9)
Summary
410(7)
Acknowledgments
411(1)
References
412(5)
Index 417

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