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Robust MIMO radar target localization via nonconvex optimization

  • Junli Liang
  • , Dong Wang
  • , Li Su
  • , Badong Chen
  • , H. Chen
  • , H. C. So
  • Northwestern Polytechnical University Xian
  • Xi'An Jiaoxtong University
  • Southwest Jiaotong University
  • City University of Hong Kong

Research output: Contribution to journalArticlepeer-review

77 Scopus citations

Abstract

This paper addresses the problem of robust target localization in distributed multiple-input multiple-output (MIMO) radar using possibly outlier range measurements. To achieve robustness against outliers, we construct an objective function for MIMO target localization via the maximum correntropy criterion. To deal with such a nonconvex and nonlinear function, we apply a half-quadratic optimization technique to determine the target position and auxiliary variables alternately. Especially, we derive a semidefinite relaxation formulation for the aforementioned position determination step. The robust performance of the developed approach is demonstrated by comparing with several conventional localization methods via computer simulation.

Original languageEnglish
Pages (from-to)33-38
Number of pages6
JournalSignal Processing
Volume122
DOIs
StatePublished - 1 May 2016

Keywords

  • Maximum correntropy criterion
  • Multiple-input multiple-output (MIMO) radar
  • Non-line-of-sight (NLOS)
  • Nonconvex optimization
  • Nonlinear optimization
  • Semidefinite relaxation
  • Target localization

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