Sparse arrays, MIMO, and compressive sensing for GMTI radar

Haley H. Kim, Alexander M. Haimovich, Mark A. Govoni

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

4 Scopus citations

Abstract

This work proposes a radar combining four synergistic elements: space-time adaptive processing (STAP), random arrays, multiple-input multiple-output (MIMO) radar, and compressive sensing. STAP supports joint space-time processing for detecting moving targets in ground clutter. Large, random arrays are undersampled arrays that support improved angle-Doppler resolution and lower minimum detectable velocity (MDV), at the cost of higher sidelobes. MIMO provides further improvements in angular resolution and MDV. Compressive sensing algorithms are designed to cope with ambiguities introduced by undersampling. We propose an algorithm for target detection and analyze its performance for detecting, slow ground targets.

Original languageEnglish (US)
Title of host publicationConference Record of the 48th Asilomar Conference on Signals, Systems and Computers
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages849-853
Number of pages5
ISBN (Electronic)9781479982974
DOIs
StatePublished - Apr 24 2015
Event48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - Pacific Grove, United States
Duration: Nov 2 2014Nov 5 2014

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2015-April
ISSN (Print)1058-6393

Other

Other48th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
CountryUnited States
CityPacific Grove
Period11/2/1411/5/14

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications

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