Sparse Autofocus Method for Maneuvering Platform High-squint SAR Based on Two-dimensional Spatial-variant Motion Compensation

The existence of high-squint angle and three-dimensional acceleration makes the motion error of maneuvering platform SAR have obvious two-dimensional spatial variability, which greatly increases the difficulty of imaging. A sparse autofocus method based on the estimation and compensation of two-dimensional spatial-variant motion error is proposed. Based on the Keystone transform and the frequency domain phase filtering method, a frequency-domain approximate observation operator is constructed to correct the spatial-variant imaging parameters. In the process of autofocus, firstly, a sparse autofocus model based on the frequency-domain approximate observation operator is constructed to focus the image roughly and estimate the non-spatial-variant motion error parameters, and the Iterative Shrinkage-Thresholding Algorithm (ISTA) is used to solve the constructed sparse autofocus model. Then, the precise phase error curves of multiple sub-regions are obtained by the sparse autofocus model and the least square method can be used to estimate the spatial-variant motion error parameters. Finally, the compensation of spatial-variant motion error is realized by correcting the approximate observation operator. The simulation results show the effectiveness of the proposed method.