An Autofocus-Coupled UAMP Method for InISAR Imaging

Compressive sensing (CS) has been successfully applied to sparse aperture (SA) interferometric inverse synthetic aperture radar (InISAR) imaging, which outperforms traditional Fourier transform-based algorithms. However, the existing CS-based algorithms generally assume that motion compensation has been completed perfectly and do not consider the effect of residual phase error (RPE) in sparse imaging, which may cause degradation of 3-D InISAR imaging performance in practical applications. To tackle this issue, an autofocus-coupled approximate message passing with unitary (AFUAMP) transformation algorithm for SA InISAR imaging is proposed in this article, which can eliminate the effect of RPE on 3-D imaging. Specifically, the phase error estimation process is introduced to the unitary approximate message passing (UAMP) framework for autofocusing, which enables UAMP to simultaneously complete inverse synthetic aperture radar (ISAR) image reconstruction and autofocus, thereby leading to excellent performance of 3-D InISAR imaging. In particular, we analyze the effect of RPE on the interferometric phase in InISAR imaging. Extensive simulation results demonstrate the effectiveness and superiority of the proposed algorithm compared to the existing algorithms.