SIMO array imaging based on compressed sensing and fast iterative shrinkage-thresholding algorithm

Yi Liao, Shuang Liu, Haomiao Xie, Houjun Sun

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

1 Citation (Scopus)

Abstract

An effective imaging approach based on compressed sensing (CS) and fast iterative shrinkage-thresholding algorithm (FISTA) is proposed to realize the two-dimensional imaging in the single-input multiple-output (SIMO) radar system. In comparison with the traditional imaging method based on matched filtering, considerable simplification of the hardware structure would come true through the implementation of the imaging method presented in this paper. It takes full advantage of the superiority of CS in signal processing to realize the sparsity of the array elements and the stepped frequency points, and restores the echo signal by FISTA, which not only preforms excellently but has enough high efficiency. In the end, the two-dimensional imaging result through numerical simulations would be presented to verify the validity and effectiveness of this particular imaging method.

Original languageEnglish
Title of host publication9th International Conference on Microwave and Millimeter Wave Technology, ICMMT 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages895-897
Number of pages3
ISBN (Electronic)9781467389815
DOIs
Publication statusPublished - 29 Nov 2016
Event9th International Conference on Microwave and Millimeter Wave Technology, ICMMT 2016 - Beijing, China
Duration: 5 Jun 20168 Jun 2016

Publication series

Name9th International Conference on Microwave and Millimeter Wave Technology, ICMMT 2016 - Proceedings
Volume2

Conference

Conference9th International Conference on Microwave and Millimeter Wave Technology, ICMMT 2016
Country/TerritoryChina
CityBeijing
Period5/06/168/06/16

Keywords

  • compressed sensing
  • fast iterative shrinkage-thresholding algorithm
  • single input multiple output (SIMO)
  • two-dimensional imaging

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