Non-Iterative Autofocus Method for High-Resolution SAR Time-Domain Imaging Based on Multi-Subimage 2D-PGA

Traditional motion compensation (MoCo) methods for high-resolution synthetic aperture radar (SAR) rely on iterative processing between imaging and MoCo, incurring heavy computational overhead and barely meeting fast imaging requirements. To address this, this paper presents a non-iterative SAR autofocus method based on multi-subimage two-dimensional phase gradient autofocus (2D-PGA). Leveraging the parallel imaging capability of the ground Cartesian back-projection (GCBP) algorithm, we reveal an a priori 2D spatially variant spectral structure of GCBP subimage errors, then the proposed 2D-PGA method is utilized to precisely estimate subimage wavenumber-domain errors. Mapping between subimage offsets and linear phase errors is derived for cross-subimage error splicing. The spliced errors are compensated for corresponding subimages to realize autofocus and ensure coherent subimage fusion, enabling non-iterative parallel processing of SAR time-domain imaging and MoCo. Experiments with 0.03 m-resolution Ku-band microwave photonic SAR measured data verify the necessity and effectiveness of the proposed method.