Global methods for compressive sensing in MIMO radar with distributed sensors

Marco Rossi, Alexander M. Haimovich, Yonina C. Eldar

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

3 Scopus citations

Abstract

We study compressive sensing methods for target localization in MIMO radar. While much attention has been given to compressive sensing of signal measurements in the time domain, this work focuses on the spatial domain. We propose a framework in which the target localization with distributed, active sensors is formulated as a nonconvex optimization. By leveraging a sparse representation, we devise a branch-and-bound type algorithm that provides a global solution to the nonconvex localization problem. It is shown that this method can achieve high resolution target localization with a highly undersampled MIMO radar with transmit/receive elements placed at random. A lower bound is developed on the number of required transmit/receive elements required to ensure accurate target localization with high probability.

Original languageEnglish (US)
Title of host publicationConference Record of the 45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011
Pages1506-1510
Number of pages5
DOIs
StatePublished - 2011
Event45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011 - Pacific Grove, CA, United States
Duration: Nov 6 2011Nov 9 2011

Publication series

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

Other

Other45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011
CountryUnited States
CityPacific Grove, CA
Period11/6/1111/9/11

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications

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