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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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationOCEANS 2013 MTS/IEEE - San Diego
Subtitle of host publicationAn Ocean in Common
PublisherIEEE Computer Society
ISBN (Print)9780933957404
DOIs
StatePublished - 2013
Event2013 MTS/IEEE San Diego Conference: An Ocean in Common, OCEANS 2013 - San Diego, CA, United States
Duration: 23 Sep 201326 Sep 2013

Publication series

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

Conference

Conference2013 MTS/IEEE San Diego Conference: An Ocean in Common, OCEANS 2013
Country/TerritoryUnited States
CitySan Diego, CA
Period23/09/1326/09/13

Keywords

  • Circular array
  • Diagonal loading
  • Optimization
  • Robust beamforming
  • Supergain

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