Volume 9 Issue 6
Dec.  2020
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Article Navigation >  Journal of Radars  > 2020  >  9(6): 1045-1055
Zhao Junxiang, Liang Xingdong, Li Yanlei. Change Detection in SAR CCD Based on the Likelihood Change Statistics[J]. Journal of Radars, 2017, 6(2): 186-194. doi: 10.12000/JR16065
Citation: SHI Tianyue, LIU Huixin, LIU Yanqi, et al. Bistatic synthetic aperture radar two-dimensional autofocus approach based on prior knowledge on phase structure[J]. Journal of Radars, 2020, 9(6): 1045–1055. doi: 10.12000/JR20048
shu

Bistatic Synthetic Aperture Radar Two-dimensional Autofocus Approach Based on Prior Knowledge on Phase Structure

DOI: 10.12000/JR20048

  • Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

Funds:  The National Natural Science Foundation of China (61671240), The Natural Science Foundation of Jiangsu (BK20170091), The Foundation of Graduate Innovation Center in Nanjing University of Aeronautics and Astronautics (kfjj20190410)
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  • Corresponding author: MAO Xinhua, Xinhua@nuaa.edu.cn
  • Received Date: 2020-04-24
  • Rev Recd Date: 2020-07-13
    • Available Online: 2020-08-06
  • Publish Date: 2020-12-28
    Abstract
  • Two-Dimensional (2-D) autofocus is an important guarantee for high-resolution imaging of airborne Synthetic Aperture Radar (SAR) under high maneuvering conditions. The existing 2-D autofocus approaches for bistatic SAR blindly estimate the phase error and do not fully utilize the prior knowledge on phase structure. In this paper, a new interpretation of the Polar Format Algorithm (PFA) for general bistatic SAR imaging is presented. From the viewpoint of Residual Cell Migration (RCM), PFA is converted into 2-D decoupling. By utilizing this new formulation, we analyze the effect of range and azimuth resampling on the residual 2-D phase error and reveal the inherent structure characteristics of the residual 2-D phase error in the wavenumber domain. The 2-D phase error estimation can reduce to one dimensional azimuth phase error estimation. Based on this prior knowledge, a structure-aided 2-D autofocus approach is proposed. Meanwhile, the information of all the data is fully excavated by averaging sub-band data when the azimuth phase error is being estimated. Compared with the existing algorithms, both the parameter estimation precision and computational efficiency are significantly improved. Experimental results clearly demonstrate the correctness of the theoretical analysis and the effectiveness of the proposed method.

     

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    • References(15)
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