Joint detection-compensation method for ISAL images of spacecraft based on global image consistency

Vibration-induced phase errors significantly degrade the imaging quality of inverse synthetic aperture lidar (ISAL), especially in low-SNR conditions and when dominant scatterers are absent. This paper proposes a joint detection-compensation framework that leverages periodic feature extraction and spatio-temporal consistency. A parametric model is developed to describe sinusoidal vibration-induced phase modulation and associated artifacts. Unlike traditional methods, the proposed approach directly processes full-aperture echoes and frames vibration compensation as a parameter inversion problem. Extensive simulations on point and satellite targets demonstrate that the proposed method outperforms conventional approaches, improving image quality, suppressing false alarms, and enhancing contrast. These results highlight the method's robustness and effectiveness for vibration compensation in ISAL.