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Adaptive Beamforming Design of Planar Arrays Based on Bayesian Compressive Sensing

文献类型：期刊论文

作者Lin, Zhenwei1; Chen, Yaowu2; Liu, Xuesong3; Jiang, Rongxin4; Shen, Binjian5
刊名IEEE SENSORS JOURNAL
出版日期2021-02-15
卷号21期号:4页码:5185-5194
关键词Covariance matrices Direction-of-arrival estimation Array signal processing Interference Estimation Planar arrays Compressed sensing Adaptive beamforming Bayesian compressed sensing covariance matrix reconstruction directions of arrival estimation side lobe control
ISSN号1530-437X
DOI10.1109/JSEN.2020.3030043
英文摘要An adaptive beamformer is effective at suppressing interference and noise. However, when the desired signal component is included in the covariance matrix, the beamformer performance becomes seriously degraded. Moreover, while the linear array has been actively researched, few studies have focused on the planar array. In this paper, an adaptive beamformer with more accurate reconstruction of the covariance matrix for a planar array is therefore proposed. The reconstruction is based on the Bayesian compressive sensing (BCS) theory. First, the directions of arrival (DOA) estimation of interferences are conducted. This problem is transformed into that of finding the minimum number of DOAs with a nonzero input because the array output is known. Accordingly, it can be converted into a probabilistic framework using the BCS technique. Then, the interference plus noise covariance matrix is reconstructed by using the DOAs of the interferences and the Capon spatial spectrum estimator. The reconstruction matrix is more accurate than other methods that directly use a data sampling matrix. Further constraints are then added to control the side-lobe level of the beam pattern of the proposed beamformer. Our numerical results confirm the effectiveness of the proposed method in terms of interference suppression, robustness to mismatch errors, and effective side-lobe-level control.
资助项目Fundamental Research Funds for the Central Universities ; National Science Foundation for Young Scientists of China[41806115] ; National Key Research and Development on Deep Ocean Technology and System[2016YFC0301604]
WOS研究方向Engineering ; Instruments & Instrumentation ; Physics
语种英语
WOS记录号WOS:000611133100125
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构Fundamental Research Funds for the Central Universities ; National Science Foundation for Young Scientists of China ; National Key Research and Development on Deep Ocean Technology and System
源URL[http://ir.idsse.ac.cn/handle/183446/8514]  
专题深海工程技术部_深海信息技术研究室
通讯作者Chen, Yaowu
作者单位1.Zhejiang Univ, Adv Digital Technol & Instrumentat, Hangzhou 310027, Zhejiang, Peoples R China
2.Zhejiang Univ, Engn Res Ctr, Embedded Syst Educ Dept, Hangzhou 310027, Zhejiang, Peoples R China
3.Zhejiang Univ, State Key Lab Ind Control Technol, Hangzhou 310027, Zhejiang, Peoples R China
4.Zhejiang Univ, Zhejiang Prov Key Lab Network Multimedia Technol, Hangzhou 310027, Zhejiang, Peoples R China
5.Chinese Acad Sci, Inst Deep Sea Sci & Engn, Haikou 572000, Hainan, Peoples R China
推荐引用方式
GB/T 7714		 Lin, Zhenwei,Chen, Yaowu,Liu, Xuesong,et al. Adaptive Beamforming Design of Planar Arrays Based on Bayesian Compressive Sensing[J]. IEEE SENSORS JOURNAL,2021,21(4):5185-5194.
APA Lin, Zhenwei,Chen, Yaowu,Liu, Xuesong,Jiang, Rongxin,&Shen, Binjian.(2021).Adaptive Beamforming Design of Planar Arrays Based on Bayesian Compressive Sensing.IEEE SENSORS JOURNAL,21(4),5185-5194.
MLA Lin, Zhenwei,et al."Adaptive Beamforming Design of Planar Arrays Based on Bayesian Compressive Sensing".IEEE SENSORS JOURNAL 21.4(2021):5185-5194.

入库方式： OAI收割

来源：深海科学与工程研究所

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