Volume 13 Issue 5
Sep.  2024
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DU Huagui, SONG Yongping, SUN Xiaoying, et al. A new approach to high-order range cell migration correction for SAR ground moving targets based on phase tracking[J]. Journal of Radars, 2024, 13(5): 955–973. doi: 10.12000/JR24122
Citation: DU Huagui, SONG Yongping, SUN Xiaoying, et al. A new approach to high-order range cell migration correction for SAR ground moving targets based on phase tracking[J]. Journal of Radars, 2024, 13(5): 955–973. doi: 10.12000/JR24122

A New Approach to High-order Range Cell Migration Correction for SAR Ground Moving Targets Based on Phase Tracking

DOI: 10.12000/JR24122 CSTR: 32380.14.JR24122
Funds:  The National Natural Science Foundation of China (62101566)
More Information
  • Corresponding author: SONG Yongping, sypopqjkl@163.com
  • Received Date: 2024-06-13
  • Rev Recd Date: 2024-07-25
  • Available Online: 2024-08-05
  • Publish Date: 2024-08-23
  • Range Cell Migration Correction (RCMC) represents an important advancement in the estimation of moving target parameters and imaging of targets in high-resolution Synthetic Aperture Radar (SAR) systems. When the motion of a target or platform becomes complex, the traditional low-order RCMC method may no longer be suitable. Meanwhile, the existing high-order RCMC method based on parameterization is susceptible to issues such as model mismatch and high computational complexity. Additionally, its performance may decrease significantly under a low Signal-to-Noise Ratio (SNR). This research utilizes Extended Kalman Filter (EKF) to track the phase responsible for RCM and develop a phase compensation function to achieve RCMC. The proposed approach is model-independent and can track high-order components in the phase, thereby enabling high-order RCMC of moving targets in SAR. In addition, EKF can filter signals during phase tracking to effectively lower the SNR threshold of the proposed method. Thus, this method offers broad applicability, moderate computational complexity, and the ability to correct non-negligible high-order residual range cell migrations, thereby distinguishing it from traditional methods. This study thoroughly explains the principles and mathematical model behind the proposed method, demonstrating its effectiveness and superiority through multiple sets of simulations and measured data processing.

     

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