Iterative robust adaptive beamforming

Abstract The minimum power distortionless response beamformer has a good interference rejection capability, but the desired signal will be suppressed if signal steering vector or data covariance matrix is not precise. The worst-case performance optimization-based robust adaptive beamformer (WCB) has...

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Main Authors: Yang Li, Hong Ma, Li Cheng
Format: Article
Language:English
Published: SpringerOpen 2017-08-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Online Access:http://link.springer.com/article/10.1186/s13634-017-0493-9
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spelling doaj-dba6ff5fd6a1403a8efce9f00b0166c22020-11-24T21:11:48ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61802017-08-012017111210.1186/s13634-017-0493-9Iterative robust adaptive beamformingYang Li0Hong Ma1Li Cheng2School of Electrical and Information Engineering, Wuhan Institute of TechnologySchool of Electric Information and Communications, Huazhong University of Science and TechnologySchool of Electrical and Information Engineering, Wuhan Institute of TechnologyAbstract The minimum power distortionless response beamformer has a good interference rejection capability, but the desired signal will be suppressed if signal steering vector or data covariance matrix is not precise. The worst-case performance optimization-based robust adaptive beamformer (WCB) has been developed to solve this problem. However, the solution of WCB cannot be expressed in a closed form, and its performance is affected by a prior parameter, which is the steering vector error norm bound of the desired signal. In this paper, we derive an approximate diagonal loading expression of WCB. This expression reveals a feedback loop relationship between steering vector and weight vector. Then, a novel robust adaptive beamformer is developed based on the iterative implementation of this feedback loop. Theoretical analysis indicates that as the iterative step increases, the performance of the proposed beamformer gets better and the iteration converges. Furthermore, the proposed beamformer does not subject to the steering vector error norm bound constraint. Simulation examples show that the proposed beamformer has better performance than some classical and similar beamformers.http://link.springer.com/article/10.1186/s13634-017-0493-9Array signal processingRobust adaptive beamformingSteering vector errorDiagonal loading
collection DOAJ
language English
format Article
sources DOAJ
author Yang Li
Hong Ma
Li Cheng
spellingShingle Yang Li
Hong Ma
Li Cheng
Iterative robust adaptive beamforming
EURASIP Journal on Advances in Signal Processing
Array signal processing
Robust adaptive beamforming
Steering vector error
Diagonal loading
author_facet Yang Li
Hong Ma
Li Cheng
author_sort Yang Li
title Iterative robust adaptive beamforming
title_short Iterative robust adaptive beamforming
title_full Iterative robust adaptive beamforming
title_fullStr Iterative robust adaptive beamforming
title_full_unstemmed Iterative robust adaptive beamforming
title_sort iterative robust adaptive beamforming
publisher SpringerOpen
series EURASIP Journal on Advances in Signal Processing
issn 1687-6180
publishDate 2017-08-01
description Abstract The minimum power distortionless response beamformer has a good interference rejection capability, but the desired signal will be suppressed if signal steering vector or data covariance matrix is not precise. The worst-case performance optimization-based robust adaptive beamformer (WCB) has been developed to solve this problem. However, the solution of WCB cannot be expressed in a closed form, and its performance is affected by a prior parameter, which is the steering vector error norm bound of the desired signal. In this paper, we derive an approximate diagonal loading expression of WCB. This expression reveals a feedback loop relationship between steering vector and weight vector. Then, a novel robust adaptive beamformer is developed based on the iterative implementation of this feedback loop. Theoretical analysis indicates that as the iterative step increases, the performance of the proposed beamformer gets better and the iteration converges. Furthermore, the proposed beamformer does not subject to the steering vector error norm bound constraint. Simulation examples show that the proposed beamformer has better performance than some classical and similar beamformers.
topic Array signal processing
Robust adaptive beamforming
Steering vector error
Diagonal loading
url http://link.springer.com/article/10.1186/s13634-017-0493-9
work_keys_str_mv AT yangli iterativerobustadaptivebeamforming
AT hongma iterativerobustadaptivebeamforming
AT licheng iterativerobustadaptivebeamforming
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