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Robust mode space supergain beamforming under unknown array mismatch

  • Yukang Liu
  • , Yong Wang
  • , Yixin Yang
  • , Zhengyao He
  • , Jinyan Du
  • University of Kentucky
  • Northwestern Polytechnical University Xian
  • Qilu University of Technology

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

The pure supergain beamformers, or MVDR beamformers have better resolution and array gain than conventional delay-and-sum beamformers (CBF), yet are highly sensitive to errors in array parameters. In this paper a robust supergain beamforming (RSBF) method is proposed for circular arrays under unknown array mismatch. The robustness of the array is considered as an optimization objective instead of constraint and it is observed the proposed robust supergain beamforming belongs to the class of diagonal loading approaches. The amount of diagonal loading can be optimally selected as a function of frequency under unknown array mismatch. A closed-form optimal solution is thus obtained for robust supergain beamforming under unknown array mismatch. Simulation results show the performance of the robust supergain beamforming surpasses the conventional beamformer and MVDR beamformer under elevated noise levels, especially at low frequencies.

源语言英语
主期刊名OCEANS 2013 MTS/IEEE - San Diego
主期刊副标题An Ocean in Common
出版商IEEE Computer Society
ISBN(印刷版)9780933957404
DOI
出版状态已出版 - 2013
活动2013 MTS/IEEE San Diego Conference: An Ocean in Common, OCEANS 2013 - San Diego, CA, 美国
期限: 23 9月 201326 9月 2013

丛书

姓名OCEANS 2013 MTS/IEEE - San Diego: An Ocean in Common

会议

会议2013 MTS/IEEE San Diego Conference: An Ocean in Common, OCEANS 2013
国家/地区美国
San Diego, CA
时期23/09/1326/09/13

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