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      Parametric Sparse Representation and Its Applications to Radar Sensing

      1 , 2

      Journal of Radars

      Chinese Academy of Sciences

      Sparse signal processing, Radar sensing, Dictionary learning

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          Abstract

          Sparse signal processing has been utilized to the area of radar sensing. Due to the presence of unknown factors such as the motion of the targets of interest and the error of the radar trajectory, a predesigned dictionary cannot provide the optimally spare representation of the actual radar signals. This paper will introduce a method called parametric sparse representation, which is a special case of dictionary learning and can dynamically learn the unknown factors during the radar sensing and achieve the optimally sparse representation of radar signals. This paper will also introduce the applications of parametric sparse representation to Inverse Synthetic Aperture Radar imaging (ISAR) imaging, Synthetic Aperture Radar imaging (SAR) autofocusing and target recognition based on micro-Doppler effect.

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          Author and article information

          Journal
          Journal of Radars
          Chinese Academy of Sciences
          01 February 2016
          : 5
          : 1
          : 1-7
          Affiliations
          [1 ] Department of Electronic Engineering, Tsinghua University
          [2 ] Department of Electrical & Computer Engineering, University of Delaware
          Article
          f07ecbe0e90841c2a93dda3bd7504068
          10.12000/JR15126

          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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