Angle-Doppler processing using sparse regularization

Ivan W. Selesnick, S. Unnikrishna Pillai, Ke Yong Li, Braham Himed

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

Abstract

The detection of moving objects on the ground by airborne radar is one application of space-time adaptive processing (STAP). The goal is to estimate the position and velocity of objects. This paper considers the problem as a linear inverse problem and uses l1-norm regularization to promote sparsity in the solution. It is proposed that the angle-Doppler plane be explicitly segmented into the clutter ridge component and a non-clutter-ridge component. We propose that the second component be modeled as sparse - as the moving objects are assumed to be well isolated in the angle-Doppler plane.

Original languageEnglish (US)
Title of host publication2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2750-2753
Number of pages4
ISBN (Print)9781424442966
DOIs
StatePublished - 2010
Event2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Dallas, TX, United States
Duration: Mar 14 2010Mar 19 2010

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
Country/TerritoryUnited States
CityDallas, TX
Period3/14/103/19/10

Keywords

  • GMTI
  • Iterated thresholding
  • Radar
  • STAP
  • Signal restoration
  • Sparsity

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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