CFAR detection for the complex approximated message passing reconstructed SAR image

Hui Bi, Bingchen Zhang, Xiao Xiang Zhu, Wen Hong, Yirong Wu

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

1 Scopus citations

Abstract

Complex approximated message passing (CAMP) is an iterative recovery algorithm for L1 regularization reconstruction which can achieve sparse and non-sparse estimations of original signal simultaneously. This paper demonstrates a CAMP-based synthetic aperture radar (SAR) image regularization reconstruction method along with a constant false alarm rate (CFAR) detection via the output non-sparse image of CAMP iterative algorithm. Compared with iterative thresholding algorithm (ITA) and orthogonal matching pursuit (OMP), the conventional L1 regularization reconstruction techniques, it not only can improve SAR image performance, but also its non-sparse estimation retains a similar background statistical distribution as conventional matched filtering (MF)-based techniques, which can be used for CFAR detection efficiently. Simulated and experimental results validate the effectiveness of the designed CFAR detector for the CAMP reconstructed SAR image.

Original languageEnglish
Title of host publication2016 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing, CoSeRa 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages133-137
Number of pages5
ISBN (Electronic)9781509029204
DOIs
StatePublished - 15 Nov 2016
Externally publishedYes
Event4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing, CoSeRa 2016 - Aachen, Germany
Duration: 19 Sep 201623 Sep 2016

Publication series

Name2016 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing, CoSeRa 2016

Conference

Conference4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing, CoSeRa 2016
Country/TerritoryGermany
CityAachen
Period19/09/1623/09/16

Keywords

  • L1 regularization
  • Synthetic aperture radar (SAR)
  • complex approximated message passing (CAMP)
  • constant false alarm rate (CFAR) detection

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