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Adaptive Beamforming Design of Planar Arrays Based on Bayesian Compressive Sensing
Lin, Zhenwei1; Chen, Yaowu2; Liu, Xuesong3; Jiang, Rongxin4; Shen, Binjian5
2021-02-15
Source PublicationIEEE SENSORS JOURNAL
ISSN1530-437X
Volume21Issue:4Pages:5185-5194
AbstractAn 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.
KeywordCovariance 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
DOI10.1109/JSEN.2020.3030043
Indexed BySCI
Funding OrganizationFundamental 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
Language英语
Funding ProjectFundamental 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 Research AreaEngineering ; Instruments & Instrumentation ; Physics
WOS SubjectEngineering, Electrical & Electronic ; Instruments & Instrumentation ; Physics, Applied
WOS IDWOS:000611133100125
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.idsse.ac.cn/handle/183446/8515
Collection深海工程技术部_深海信息技术研究室
Corresponding AuthorChen, Yaowu
Affiliation1.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
Recommended Citation
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.
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