Parameter Estimation and Motion Compensation for Maneuvering Target ISAR Imaging

Due to the non-stationary motion of non-cooperative targets during the coherent integration time in inverse synthetic aperture radar (ISAR) imaging, the Doppler modulation is changed over time, leading to high order phase errors. Traditional imaging models and algorithms are no longer applicable. To address this issue, this paper proposes a motion compensation algorithm based on motion parameter estimation, which achieves well-focused image and accurate image calibration. Firstly, considering the uniformly accelerated rotation of the target and the unknown position of the rotation center, the signal model for maneuverable targets is established. Then, the target parameters are estimated using the image minimum entropy method, and phase errors are eliminated through phase compensation. Simultaneously, image calibration is completed using the estimated rotation parameters. Finally, the effectiveness of the proposed algorithm is verified through experiments using measured data.