Coherent MIMO radar with sparse recovery: Joint vs. separate range and azimuth estimation

Lorenz Weiland, Thomas Wiese, Wolfgang Utschick

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

2 Scopus citations

Abstract

An optimal joint estimation of the ranges, azimuth angles, and reflection coefficients for multiple targets in coherent multiple-input multiple-output radar is computationally intractable. We provide a numerical comparison of different estimators that all use sparse recovery for the discretized range parameter to reduce algorithmic complexity. The methods differ in whether estimation of angles and ranges is performed jointly or separately and in whether the azimuth angle is discretized, too. Our results show that joint estimators perform better than separate estimators and that introducing an angular grid adds robustness for low SNR values, but decreases accuracy for high SNR values.

Original languageEnglish
Title of host publicationConference Record of the 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages594-598
Number of pages5
ISBN (Electronic)9781467385763
DOIs
StatePublished - 26 Feb 2016
Event49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - Pacific Grove, United States
Duration: 8 Nov 201511 Nov 2015

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2016-February
ISSN (Print)1058-6393

Conference

Conference49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
Country/TerritoryUnited States
CityPacific Grove
Period8/11/1511/11/15

Keywords

  • MIMO radar
  • block sparsity
  • compressed sensing
  • imaging
  • sparse recovery

Fingerprint

Dive into the research topics of 'Coherent MIMO radar with sparse recovery: Joint vs. separate range and azimuth estimation'. Together they form a unique fingerprint.

Cite this