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      CS-SAR Imaging Method Based on Inverse Omega-K Algorithm

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          Abstract

          Compressed Sensing (CS) has been proved to be effective in Synthetic Aperture Radar (SAR) imaging. Previous CS-SAR imaging algorithms are very time consuming, especially for producing high-resolution images. In this study, we propose a new CS-SAR imaging method based on the well-known omega-K algorithm, which is precise and convenient to use in SAR imaging. First, we derive an inverse omega-K algorithm to directly obtain echoes without any convolution between the transmitted signal and scene. Then, we formulate the SAR imaging problem into a sparse regularization problem and solve it using an iterative thresholding algorithm. With our derived inverse omega-K algorithm, we can save significant amounts of computation time and computer memory usage. Simulation results show that the proposed method can effectively recover SAR images with much less data than that required by the Nyquist rate.

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          Author and article information

          Journal
          Journal of Radars
          Chinese Academy of Sciences
          01 February 2017
          : 6
          : 1
          : 25-33
          Affiliations
          [1 ] ①(Department of EEIS, University of Science and Technology of China, Hefei 230027, China) ②(Key Laboratory of Electromagnetic Space Information, Chinese Academy of Sciences, Hefei 230027, China)
          Article
          c5d3f70ff1ab4818b2fbd5c6ce34e42d
          10.12000/JR16027

          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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