Robust rank constrained kronecker covariance matrix estimation

A. Breloy, Y. Sun, P. Babu, G. Ginolhac, D. P. Palomar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we consider the problem of robustly estimating a structured covariance matrix (CM). Specifically, we focus on CM structures that involve Kronecker products of low rank matrices, which often arise in the context of array processing (e.g. in MIMO-Radar, COLD array, and STAP). To tackle this problem, we derive a new Constrained Tyler's Estimators (CTE), which is defined as the minimizer of the cost function associated to Tyler's estimator under Kronecker structural constraint. Algorithms to compute these new CTEs are derived based on the Majorization-Minimization algorithmic framework.

Original languageEnglish (US)
Title of host publicationConference Record of the 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages810-814
Number of pages5
ISBN (Electronic)9781538639542
DOIs
StatePublished - Mar 1 2017
Event50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016 - Pacific Grove, United States
Duration: Nov 6 2016Nov 9 2016

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Other

Other50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016
CountryUnited States
CityPacific Grove
Period11/6/1611/9/16

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications

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