MIMO-sparse radars for enhanced DOA estimation of spatio-temporal correlated sources

Navid Amani, Venkat Roy, Alessio Filippi, Rob Maaskant

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

Abstract

This paper investigates an enhanced direction-of-arrival (DOA) estimation problem of spatio-temporal correlated sources when a multiple-input multiple-output (MIMO) sparse radar is deployed. A virtual array with increased degrees-of-freedom (DOF) is realized within two steps by combining MIMO radar with the Khatri-Rao (KR) product approach. Since the final virtual array is a uniform linear array (ULA), a well-known spatial smoothing algorithm is applied to reinforce the rank of its covariance matrix. Meanwhile, the enhanced DOF results in a higher spatial resolution of the radar in the context of DOA estimation.

Original languageEnglish
Title of host publicationProceedings of the 2019 9th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2019
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages243-246
Number of pages4
ISBN (Electronic)978-1-7281-0566-6
DOIs
Publication statusPublished - 1 Sep 2019
Event9th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2019 - Granada, Spain
Duration: 9 Sep 201913 Sep 2019

Conference

Conference9th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications, APWC 2019
CountrySpain
CityGranada
Period9/09/1913/09/19

Keywords

  • DOA estimation
  • Khatri-Rao subspace
  • MIMO radar
  • sparse array

Fingerprint Dive into the research topics of 'MIMO-sparse radars for enhanced DOA estimation of spatio-temporal correlated sources'. Together they form a unique fingerprint.

Cite this