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Sparse Three-dimensional Imaging Based on Hough Transform for Forward-looking Array SAR in Low SNR

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      Abstract

      The performance of sparse reconstruction algorithm of compressive sensing in low Signal-to-Noise Ratio (SNR) is lower, and the quality of sparse three-dimensional imaging for forward-looking array synthetic aperture radar in low SNR is reduced greatly. To solve this problem, a validate method of reconstruction algorithm of compressive sensing based on Hough transform is proposed, in which the continuity of the scattering coefficient vector in the two-dimensional space of range direction and slant range direction and the straight line detection method of Hough transform is used, and thus the reconstruction quality of compressive sensing is increased effectively. Also, the simulation experiments indicate that this method can improve the sparse three-dimensional imaging for forward-looking array SAR in low SNR effectively.

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      Affiliations
      [1] (Xi’an Communications Institute, Xi’an710106, China)
      Journal
      Journal of Radars
      Chinese Academy of Sciences
      01 June 2017
      : 6
      : 3
      : 316-323
      e59fcdde8d5c469fb1491442f3061cf3
      10.12000/JR17011

      This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

      Categories
      Technology (General)
      T1-995
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