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Volume 40 Issue 11
Oct.  2018
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Huan DENG, Yachao LI, Haiwen MEI, Yinghui QUAN, Mengdao XING. New Back-filtering PFA Imaging Algorithm and Distortion Correction Method for Missile-borne Bistatic SAR with Curved Track[J]. Journal of Electronics & Information Technology, 2018, 40(11): 2638-2644. doi: 10.11999/JEIT170994
Citation: Huan DENG, Yachao LI, Haiwen MEI, Yinghui QUAN, Mengdao XING. New Back-filtering PFA Imaging Algorithm and Distortion Correction Method for Missile-borne Bistatic SAR with Curved Track[J]. Journal of Electronics & Information Technology, 2018, 40(11): 2638-2644. doi: 10.11999/JEIT170994

New Back-filtering PFA Imaging Algorithm and Distortion Correction Method for Missile-borne Bistatic SAR with Curved Track

doi: 10.11999/JEIT170994
Funds:  The National Natural Science Foundation of China (61001211, 61303035, 61471283)
  • Received Date: 2017-10-24
  • Rev Recd Date: 2018-08-13
  • Available Online: 2018-08-20
  • Publish Date: 2018-11-01
  • The traditional bistatic equivalent range model has low accuracy and make the traditional Polar Format Algorithm (PFA) are inapplicable in missile-borne bistatic Synthetic Aperture Radar (SAR) imaging with curved track due to the existing of three-axis velocity and acceleration. In addition, due to the existing of space-variant motion error introduced by acceleration, the traditional 2-D sub-block compensation method will cause the discontinuities between the image sub-blocks, thus affecting the subsequent image matching application. In view of these problems, this paper proposes a Back-Filtering PFA algorithm (BFPFA) which is based on the Improved Generalized Bistatic Equivalent Range Model (IGBERM). Constructing the combined compensating filter of space-variant phase error and geometric distortion, as well as reverse mapping interpolation, can realize the combined compensation of motion error, wavefront bending and geometric distortion in the process of oblique conversion, and obtain the SAR distance map without distortion, which is more conducive to the subsequent image matching applications. Finally, the simulations validate the effectiveness of the proposed algorithm.
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