Synthetic aperture radar autofocus via semidefinite relaxation

Kuang Hung Liu*, Ami Wiesel, David C. Munson

*Corresponding author for this work

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

7 Scopus citations

Abstract

Synthetic Aperture Radar (SAR) imaging can suffer from image focus degradation due to unknown platform or target motion. Autofocus algorithms use signal processing techniques to remove the undesired phase errors. The recently proposed multichannel autofocus models formulate the problem as the solution to Ae ≈ 0, where A is a given matrix and φ are the unknown phases. Previous methods approximated e using the null vector of A. We propose to approximate e using conic optimization and call this new autofocus algorithm Semidefinite Relaxation Autofocus (SDRA). Experimental results using a simulated SAR image shows that SDRA has promising performance advantages over existing autofocus methods.

Original languageAmerican English
Title of host publication2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1342-1345
Number of pages4
ISBN (Print)9781424442966
DOIs
StatePublished - 2010
Externally publishedYes
Event2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Dallas, TX, United States
Duration: 14 Mar 201019 Mar 2010

Publication series

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

Conference

Conference2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
Country/TerritoryUnited States
CityDallas, TX
Period14/03/1019/03/10

Keywords

  • Autofocus
  • Fourier-domain multichannel autofocus
  • Semidefinite relaxation
  • Synthetic aperture radar
  • Wide-angle SAR

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