Quaternion-based worst case constrained beamformer based on electromagnetic vector-sensor arrays

Xirui Zhang, Wei Liu, Yougen Xu, Zhiwen Liu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

12 Citations (Scopus)

Abstract

A robust adaptive beamforming scheme based on two-component electromagnetic (EM) vector-sensor arrays is proposed by extending the well-known worst-case constraint into the quaternionic domain. After defining the uncertainty set of the desired signal's quaternionic steering vector, two quaternion-based constrained minimization problems are derived. We then reformulate them into two real-valued convex quadratic problems, which can be easily solved via the second-order cone (SOC) programming approach. Numerical simulations show that our quaternion-based robust beamformer significantly outperforms the sample matrix inversion minimum variance distortionless response (SMI-MVDR) beamformer and the quaternion Capon (Q-Capon) beamformer in the presence of steering vector mismatches.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages4149-4153
Number of pages5
DOIs
Publication statusPublished - Oct 2013
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: 26 May 201331 May 2013

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
Country/TerritoryCanada
CityVancouver, BC
Period26/05/1331/05/13

Keywords

  • quaternion
  • Robust adaptive beamformer
  • vector-sensor array
  • worst case constraint

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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