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A novel SAR imaging processing algorithm based on compressive sensing

  • Qinghu Meng*
  • , Chunsheng Li
  • , Huaping Xu
  • *Corresponding author for this work
  • Beihang University

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

Abstract

Synthetic aperture radar (SAR) is a remote sensing system producing images with high resolution. It is not influenced by time and weather. As the increase of resolution and bandwidth, the volume of data augments sharply, bringing great difficulties to store, transmission and processing. Nowadays there is a novel theory named Compressive Sensing (CS) which can recover signal with few samples. Its sample rate is lower than Nyquist rate. In this paper, a novel CS-based SAR imaging algorithm is proposed, in which a random Gaussian measurement matrix, a constructed sparsity matrix and OMP algorithm are employed. The new algorithm can largely reduce the number of samples. The simulation results show the feasibility of the proposed algorithm.

Original languageEnglish
Title of host publication2011 3rd International Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2011
Pages684-687
Number of pages4
StatePublished - 2011
Event2011 3rd International Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2011 - Seoul, Korea, Republic of
Duration: 26 Sep 201130 Sep 2011

Publication series

Name2011 3rd International Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2011

Conference

Conference2011 3rd International Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2011
Country/TerritoryKorea, Republic of
CitySeoul
Period26/09/1130/09/11

Keywords

  • Compressed Sensing (CS)
  • SAR
  • Sampling Rate

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