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FU Jixiang, ZHANG Chao, XING Wenjie, et al. Fast space-variant phase error compensation and geometric correction for bistatic ISAR imaging using a modified newton’s method[J]. Journal of Radars, in press. doi: 10.12000/JR25052
Citation: FU Jixiang, ZHANG Chao, XING Wenjie, et al. Fast space-variant phase error compensation and geometric correction for bistatic ISAR imaging using a modified newton’s method[J]. Journal of Radars, in press. doi: 10.12000/JR25052
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Fast Space-variant Phase Error Compensation and Geometric Correction for Bistatic ISAR Imaging Using a Modified Newton’s Method

DOI: 10.12000/JR25052 CSTR: 32380.14.JR25052
  • 1.

    School of Information Mechanics and Sensing Engineering, Xidian University, Xi’an 710071, China

  • 2.

    National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China

  • 3.

    Key Laboratory for Information Science of Electromagnetic Waves (MoE), Fudan University, Shanghai 200438, China

  • 4.

    Beijing Institute of Radio Measurement, Beijing 100089, China

Funds:  The Young Scientist Fund of the National Natural Science Foundation of China (62301389), The Key Program of National Natural Science Foundation of China (62331020), The National Nature Science Foundation of China (U22B2015), The National Key R&D Program of China (2022YFB3901604), Shaanxi Province Science and Technology Innovation Team (2025RS-CXTD-002)
More Information
  • Corresponding author: FU Jixiang, jxfu@xidian.edu.cn
  • Received Date: 2025-03-24
  • Rev Recd Date: 2025-07-04
    • Available Online: 2025-07-10
    Abstract
  • Bistatic Inverse Synthetic Aperture Radar (Bi-ISAR) has garnered significant attention in the military and civilian domains due to its superior stealth and antijamming capabilities. However, the changing bistatic angle during Bi-ISAR imaging causes space-variant defocusing and geometric distortion in the resulting images, thereby severely compromising the accuracy of subsequent information extraction and target recognition. To address these issues, this study proposes a fast space-variant phase error compensation and geometric correction method for Bi-ISAR imaging based on a modified Newton’s method. This method uses the image entropy of the Bi-ISAR imaging result as the cost function and introduces space-variant coefficients and rotation parameters as optimization variables to formulate an optimization equation. By modifying the traditional Newton’s method to ensure the positive definiteness of the Hessian matrix, the cost function is guaranteed to be optimized along the descent direction in each iteration. Solving this optimization equation to minimize image entropy simultaneously estimates the rotation parameters, which are then used to construct a geometric correction function and calculate the scaling factor, that is, the actual size of each grid in the image, enabling geometric correction and scaling of the final imaging result. The proposed method simultaneously corrects space-variant phase errors and geometric distortion and operates in a data-driven manner, requiring only low initial image quality. Furthermore, due to the quadratic convergence property of Newton’s method, the proposed method offers higher computational efficiency compared with other methods. Finally, the effectiveness of the proposed method is validated through the processing and comparative analysis of the point target simulation, electromagnetic calculation, and ground real target experimental data.

     

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