In the corner reflector jamming scenario, the ship target and the corner reflector array have different degrees of defocusing in the synthetic aperture radar (SAR) image due to their complex motions, which is unfavorable to the subsequent target recognition. In this manuscript, we propose an imaging method for marine targets based on time–frequency analysis with the modified Clean technique. Firstly, the motion models of the ship target and the corner reflector array are established, and the characteristics of their Doppler parameter distribution are analyzed. Then, the Chirp Rate–Quadratic Chirp Rate Distribution (CR-QCRD) algorithm is utilized to estimate the Doppler parameters. To address the challenges posed by the aggregated scattering points of the ship target and the overlapping Doppler histories of the corner reflector array, the Clean technique is modified by short-time Fourier transform (STFT) filtering and amplitude–phase distortion correction using fractional Fourier transform (FrFT) filtering. This modification aims to improve the accuracy and efficiency of extracting scattering point components. Thirdly, in response to the poor universality of the traditional Clean iterative termination condition, the kurtosis of the residual signal spectrum amplitude is adopted as the new iterative termination condition. Compared with the existing imaging methods, the proposed method can adapt to the different Doppler distribution characteristics of the ship target and the corner reflector array, thus realizing better robustness in obtaining a well-focused target image. Finally, simulation experiments verify the effectiveness of the algorithm.

HRWS (high resolution and wide swath, HRWS) SAR always suffers channel phase error in the multichannel reconstruction stage and results in a lower imaging quality. The image domain error estimation method can achieve superior performance by utilizing the signal-to-noise ratio (SNR) advantage. Nevertheless, in practice, the inevitable baseline error in HRWS SAR will lead to the inability of multichannel images to be registered in azimuth time and reduction of the channel phase error estimation accuracy. Considering that the joint-pixel model can fully contain the coherent information in such a case, a novel multichannel phase error estimation method is proposed. In this paper, by establishing a multichannel signal model in the image domain, an image domain subspace-based phase error estimation method based on joint-pixel selection and vector construction is derived. The proposed method can weaken the influence of subspace estimation inaccuracy caused by the inaccurate azimuth baseline and avoid the large amount of calculation caused by iterative elimination of baseline error and phase error in traditional algorithms, thus further improving computational efficiency. Simulation experiments and real acquired HRWS SAR data processing validate the estimation accuracy of the proposed method.