Volume 9 Issue 5
Oct.  2020
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LI Hang, LIU Wenkang, SUN Guangcai, et al. MEO SAR imaging based on imaging coordinate system optimization[J]. Journal of Radars, 2020, 9(5): 856–864. doi: 10.12000/JR20098
Citation: LI Hang, LIU Wenkang, SUN Guangcai, et al. MEO SAR imaging based on imaging coordinate system optimization[J]. Journal of Radars, 2020, 9(5): 856–864. doi: 10.12000/JR20098

MEO SAR Imaging Based on Imaging Coordinate System Optimization

doi: 10.12000/JR20098
Funds:  The State Key Program of National Natural Science China (61931025), The 111 Project (B18039)
More Information
  • Corresponding author: LIU Wenkang, wkliu@stu.xidian.edu.cn; SUN Guangcai, rsandsgc@126.com
  • Received Date: 2020-07-08
  • Rev Recd Date: 2020-09-15
  • Available Online: 2020-10-09
  • Publish Date: 2020-10-28
  • In the Medium-Earth-Orbit Synthetic Aperture Radar (MEO SAR), the curved trajectory and long synthetic aperture time lead to a two-dimensional spatial variation in the signals. Traditional methods usually process the range and azimuth variations separately, and the computational complexities are high. Herein, we study the Doppler rate distribution across a large scene and propose a non-orthogonal and nonlinear coordinate system wherein the MEO SAR signals satisfy the azimuth-shift–invariant property. Thus, the efficiency of the image formation processor can be significantly improved. The higher-order Doppler parameters are addressed by the Doppler linearization. Then, more precise focusing can be achieved, and the azimuth time-shift caused by the changes in signal distribution is addressed. Finally, the processing results of simulated stripmap-mode data with a 2-m resolution are presented to validate the effectiveness of the proposed algorithm.

     

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