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A novel approach for autofocus in spaceborne SAR based on low-order polynomial orbit model and contrast maximization

CHEN Ying1,2,3, MENG Dadi1,2†, LI Guangzuo1,2, HUANG Lijia1,2, LI Yingying4, XIN Yu4   

  1. 1 Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China;
    2 Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Chinese Academy of Sciences, Beijing 100190, China;
    3 School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China;
    4 Beijing Institute of Remote Sensing Information, Beijing 100192, China
  • Received:2023-02-13 Revised:2023-04-11

Abstract: Spaceborne SAR imagery with higher spatial resolutions requires greater knowledge of the satellite's orbit. However, sometimes GPS systems are not available to provide accurate position information that the image resolution requires. In our experience, the smoothness of spaceborne SAR orbit can provide help for autofocus. In this paper, a novel approach for autofocusing in spaceborne SAR is proposed. First, the modeling of the orbit in three-dimensional as polynomial functions is involved. Therefore, autofocusing can be achieved by estimating the polynomial coefficients. Then, several patches distributed over the SAR image are selected, and the optimal range history of the center point in each patch is obtained based on the maximum-contrast optimization. The estimated orbit of the whole scene can be derived through the range history information. Finally, the image can be refined with better focusing performance. The estimated orbit is capable of satisfying the optimal quality for every patch. Furthermore, with proper patch selection, including the number and the relative location of patches, better quality within the whole scene can be reconstructed by the estimated orbit. This method is tested and validated with simulation experiments and real data.

Key words: spaceborne synthetic aperture radar (SAR), autofocus, orbit error, contrast maximization

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