A novel 2D complex FISTA for ISAR imaging

Spare recovery or compressed sensing (CS) paved a new way to break the resolution limitation of the FFT in ISAR imaging. However, the ISAR echoes are 2D complex matrix with arbitrary sparse structure. It was usually time consuming when obtained the ISAR image using the conventional recovery algorithms. To further accelerate the sparse recovery speed of ISAR imaging, we proposed a novel 2D complex fast iterative shrinkage-thresholding algorithm (CFISTA) for ISAR imaging in a parallel way. First, the core procedure of the CFISTA is deduced. Subsequently, it can be extended to complex domain. Finally, a high resolution ISAR image can be obtained. Numerical results based on simulated and real data show that the proposed algorithm can not only acquire a clear ISAR image but also recover the image more efficiently than column-by-column recovery.