SAR autofocus using wiener deconvolution

Lijuan Liu*, Xia Bai, Juan Zhao, Ran Tao

*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

This paper proposes a new approach to synthetic aperture radar (SAR) autofocus. The proposed metric-based autofocus algorithm is based on the Wiener deconvolution filter, which has the advantage of the phase error compensation as well as noise suppression. The sharpness metrics are used to measure the degree of the focus of the SAR image. To compare the performance of the metric-based SAR autofocus, we also present a detailed analysis of different sharpness metrics. Then, a guide about the optimal sharpness metric in various SAR scenes is presented. The simulation results with the real data demonstrate that the proposed algorithm has better restoration capability in comparison with conventional minimum-entropy algorithm.

Original languageEnglish
Title of host publicationProceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010
Pages1256-1259
Number of pages4
DOIs
Publication statusPublished - 2010
Event1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010 - Harbin, China
Duration: 17 Sept 201019 Sept 2010

Publication series

NameProceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010

Conference

Conference1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010
Country/TerritoryChina
CityHarbin
Period17/09/1019/09/10

Keywords

  • Autofocus
  • SAR
  • Sharpness metrics
  • Wiener deconvolution

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