TY - GEN
T1 - Robust adaptive beamforming for general-rank signal models using worst-case performance optimization
AU - Shahbazpanahi, Shahram
AU - Gershman, Alex B.
AU - Luo, Zhi Quan
AU - Wong, Kon Max
N1 - Publisher Copyright:
© 2002 IEEE.
Copyright:
Copyright 2015 Elsevier B.V., All rights reserved.
PY - 2002
Y1 - 2002
N2 - The performance of adaptive beamforming methods is known to degrade in the presence of even small mismatches between the actual and presumed array responses to the desired signal. In this paper, we propose a new powerful approach to robust adaptive beamforming in the presence of unknown arbitrary-type mismatches of the desired signal array response. Our approach is developed for the most general case of an arbitrary dimension of the desired signal subspace and is applicable to both rank-one and higher-rank desired signal models. The proposed beamformer is based on an explicit modeling of uncertainties in the desired signal array response and data covariance matrix as well as worst-case performance optimization. Simple closed-form solution to this robust adaptive beamforming problem is obtained. This solution naturally combines two different types of diagonal loading which are applied to the sample and presumed signal covariance matrices. Our new robust beamformer has a computational complexity comparable to that of the traditional adaptive beamforming algorithms while offers a greatly improved robustness and faster convergence rate as compared to existing robust beamformers.
AB - The performance of adaptive beamforming methods is known to degrade in the presence of even small mismatches between the actual and presumed array responses to the desired signal. In this paper, we propose a new powerful approach to robust adaptive beamforming in the presence of unknown arbitrary-type mismatches of the desired signal array response. Our approach is developed for the most general case of an arbitrary dimension of the desired signal subspace and is applicable to both rank-one and higher-rank desired signal models. The proposed beamformer is based on an explicit modeling of uncertainties in the desired signal array response and data covariance matrix as well as worst-case performance optimization. Simple closed-form solution to this robust adaptive beamforming problem is obtained. This solution naturally combines two different types of diagonal loading which are applied to the sample and presumed signal covariance matrices. Our new robust beamformer has a computational complexity comparable to that of the traditional adaptive beamforming algorithms while offers a greatly improved robustness and faster convergence rate as compared to existing robust beamformers.
UR - http://www.scopus.com/inward/record.url?scp=84949226715&partnerID=8YFLogxK
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U2 - 10.1109/SAM.2002.1190990
DO - 10.1109/SAM.2002.1190990
M3 - Conference contribution
AN - SCOPUS:84949226715
T3 - Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
SP - 13
EP - 17
BT - 2002 IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings, SAME 2002
PB - IEEE Computer Society
T2 - IEEE Sensor Array and Multichannel Signal Processing Workshop, SAME 2002
Y2 - 4 August 2002 through 6 August 2002
ER -