Robust adaptive beamforming

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Publication Information:

Hoboken, NJ : John Wiley and Sons, 2006

ISBN:

9780471678502

Subject Term:

Adaptive antennas

Antenna radiation patterns

Added Author:

Li, Jian

Stoica, Petre

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Library	Item Barcode	Call Number	Material Type	Item Category 1	Status
Searching... PSZ JB	30000004615781	TK7871.67.A33 R63 2006	Open Access Book	Book	Searching... Unknown

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 Notes

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.

Robert G. Lorenz and Stephen P. BoydAlex B. Gershman and Zhi-Quan Luo and Shahram ShahbazpanahiJian Li and Petre Stoica and Zhisong WangXavier Mestre and Miguel A. LagunasYonina C. Eldar and Arye NehoraiAlle-Jan van der Veen and Amir LeshemElio D. Di Claudio and Raffaele Parisi

Contributors	p. ix
Preface	p. xi
1 Robust Minimum Variance Beamforming	p. 1
1.1 Introduction	p. 1
1.2 A Practical Example	p. 8
1.3 Robust Weight Selection	p. 12
1.4 A Numerical Example	p. 23
1.5 Ellipsoidal Modeling	p. 28
1.6 Uncertainty Ellipsoid Calculus	p. 31
1.7 Beamforming Example with Multiplicative Uncertainties	p. 41
1.8 Summary	p. 44
Appendix Notation and Glossary	p. 44
References	p. 45
2 Robust Adaptive Beamforming Based on Worst-Case Performance Optimization	p. 49
2.1 Introduction	p. 49
2.2 Background and Traditional Approaches	p. 51
2.3 Robust Minimum Variance Beamforming Based on Worst-Case Performance Optimization	p. 60
2.4 Numerical Examples	p. 74
2.5 Conclusions	p. 80
Appendix 2.A Proof of Lemma 1	p. 81
Appendix 2.B Proof of Lemma 2	p. 81
Appendix 2.C Proof of Lemma 3	p. 82
Appendix 2.D Proof of Lemma 4	p. 84
Appendix 2.E Proof of Lemma 5	p. 85
References	p. 85
3 Robust Capon Beamforming	p. 91
3.1 Introduction	p. 91
3.2 Problem Formulation	p. 93
3.3 Standard Capon Beamforming	p. 95
3.4 Robust Capon Beamforming with Single Constraint	p. 96
3.5 Capon Beamforming with Norm Constraint	p. 112
3.6 Robust Capon Beamforming with Double Constraints	p. 116
3.7 Robust Capon Beamforming with Constant Beamwidth and Constant Powerwidth	p. 133
3.8 Rank-Deficient Robust Capon Filter-Bank Spectral Estimator	p. 148
3.9 Adaptive Imaging for Forward-Looking Ground Penetrating Radar	p. 166
3.10 Summary	p. 185
Acknowledgments	p. 185
Appendix 3.A Relationship between RCB and the Approach in [14]	p. 185
Appendix 3.B Calculating the Steering Vector	p. 188
Appendix 3.C Relationship between RCB and the Approach in [15]	p. 189
Appendix 3.D Analysis of Equation (3.72)	p. 190
Appendix 3.E Rank-Deficient Capon Beamformer	p. 191
Appendix 3.F Conjugate Symmetry of the Forward-Backward FIR	p. 193
Appendix 3.G Formulations of NCCF and HDI	p. 194
Appendix 3.H Notations and Abbreviations	p. 195
References	p. 196
4 Diagonal Loading for Finite Sample Size Beamforming: An Asymptotic Approach	p. 201
4.1 Introduction and Historical Review	p. 202
4.2 Asymptotic Output SINR with Diagonal Loading	p. 213
4.3 Estimating the Asymptotically Optimum Loading Factor	p. 225
4.4 Characterization of the Asymptotically Optimum Loading Factor	p. 236
4.5 Summary and Conclusions	p. 243
Acknowledgments	p. 243
Appendix 4.A Proof of Proposition 1	p. 243
Appendix 4.B Proof of Lemma 1	p. 246
Appendix 4.C Derivation of the Consistent Estimator	p. 247
Appendix 4.D Proof of Proposition 2	p. 249
References	p. 254
5 Mean-Squared Error Beamforming for Signal Estimation: A Competitive Approach	p. 259
5.1 Introduction	p. 259
5.2 Background and Problem Formulation	p. 261
5.3 Minimax MSE Beamforming for Known Steering Vector	p. 271
5.4 Random Steering Vector	p. 281
5.5 Practical Considerations	p. 284
5.6 Numerical Examples	p. 285
5.7 Summary	p. 294
Acknowledgments	p. 295
References	p. 296
6 Constant Modulus Beamforming	p. 299
6.1 Introduction	p. 299
6.2 The Constant Modulus Algorithm	p. 303
6.3 Prewhitening and Rank Reduction	p. 307
6.4 Multiuser CMA Techniques	p. 312
6.5 The Ahalytical CMA	p. 315
6.6 Adaptive Prewhitening	p. 325
6.7 Adaptive ACMA	p. 328
6.8 DOA Assisted Beamforming of Constant Modulus Signals	p. 338
6.9 Concluding Remarks	p. 347
Acknowledgment	p. 347
References	p. 347
7 Robust Wideband Beamforming	p. 353
7.1 Introduction	p. 353
7.2 Notation	p. 357
7.3 Wideband Array Signal Model	p. 358
7.4 Wideband Beamforming	p. 363
7.5 Robustness	p. 369
7.6 Steered Adaptive Beamforming	p. 381
7.7 Maximum Likelihood STBF	p. 389
7.8 ML-STBF Optimization	p. 393
7.9 Special Topics	p. 399
7.10 Experiments	p. 401
7.11 Summary	p. 410
Acknowledgments	p. 411
References	p. 412
Index	p. 417

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