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      Four-dimensional SAR Imaging Algorithm Based on Iterative Reconstruction of Magnitude and Phase

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          Abstract

          Observation data obtained from the Four-Dimensional (4D) Synthetic Aperture Radar (SAR) system is sparse and non-uniform in the baseline-time plane. Hence, the imaging results acquired by traditional Fourier-based methods are limited by high side lobes. Compressive Sensing (CS) is a recently proposed technique that allows for the recovery of an unknown sparse signal with overwhelming probability from very limited samples. However, the standard CS framework has been developed for real-valued signals, and the imaging process for 4D synthetic aperture radar deals with complex-valued data. In this study, we propose a new 4D synthetic aperture radar imaging algorithm based on an iterative reconstruction of magnitude and phase, which transforms the height-velocity imaging problem of 4D synthetic aperture radar into a joint reconstruction problem of the magnitude and phase of the complex-valued scatter coefficient. Using the phase information in the algorithm, the image quality is improved. Simulation results confirm the effectiveness of the proposed method.

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          Author and article information

          Journal
          Journal of Radars
          Chinese Academy of Sciences
          01 February 2016
          : 5
          : 1
          : 65-71
          Affiliations
          [1 ] College of Information Science and Engineering, Henan University of Technology
          [2 ] The Institute of Electronics, Chinese Academy of Sciences
          Article
          c1ec21c887654e88b6b37abf9dd25500
          10.12000/JR15135

          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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