Volume 11 Issue 6
Dec.  2022
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Article Contents
CHEN Jianlai, XIONG Yi, XU Gang, et al. Nonlinear trajectory synthetic aperture radar imaging and autofocus algorithm based on sub-image nonlinear chirp scaling[J]. Journal of Radars, 2022, 11(6): 1098–1109. doi: 10.12000/JR22171
Citation: CHEN Jianlai, XIONG Yi, XU Gang, et al. Nonlinear trajectory synthetic aperture radar imaging and autofocus algorithm based on sub-image nonlinear chirp scaling[J]. Journal of Radars, 2022, 11(6): 1098–1109. doi: 10.12000/JR22171

Nonlinear Trajectory Synthetic Aperture Radar Imaging and Autofocus Algorithm Based on Sub-image Nonlinear Chirp Scaling

doi: 10.12000/JR22171
Funds:  The National Natural Science Foundation of China (61901531, 62271510, 62105372, 62171475)
More Information
  • Corresponding author: CHEN Jianlai, jianlaichen@163.com; XIONG Yi, XY639692@163.com
  • Received Date: 2022-08-23
  • Rev Recd Date: 2022-11-16
  • Available Online: 2022-11-21
  • Publish Date: 2022-11-24
  • The radar echo signal may experience substantial two-dimensional spatial variance due to the nonlinear Synthetic Aperture Radar (SAR) trajectory. The traditional frequency-domain imaging algorithms based on the assumption of azimuth translational invariance are unsuitable for high-precision imaging of nonlinear trajectory SAR. Therefore, for nonlinear trajectory SAR imaging, the azimuth spatial variance of the echo signals is typically rectified using complex Nonlinear Chirp Scaling (NCS). However, when there are substantial motion errors, it cannot be effectively combined with the current autofocus algorithms considering the complexity of the algorithm due to too many NCS parameters. Thus, to address this issue, this study proposes a nonlinear trajectory SAR imaging and autofocus method according to the sub-image NCS, which can reduce the number of NCS parameters and ensure imaging accuracy; moreover, it is more conducive to the subsequent autofocus processing. The effectiveness of the suggested approach is confirmed by simulation and measured data processing.

     

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