An autofocus approach for model error correction in compressed sensing SAR imaging

This paper presents an iterative autofocus approach to improve the performance of compressed sensing (CS) in synthetic aperture radar (SAR) imaging in the case of model error. Combined with the least square (LS) regularization technique and the minimum mean square error (MMSE) focusing method, the approach can solve a joint optimization problem to achieve model error parameter estimation and SAR image formation simultaneously. In each iterative of the approach, the SAR observation model is updated with the sensor platform positions obtained by a MMSE-based focusing cost function, after that, the image is reconstructed by LS regularization technique with the updated observation model. Numerical simulation results demonstrate the effectiveness of the approach for CS-based SAR imaging with observation model error.