MIMO Array SAR Fast 3-D Imaging Based on Sparse Signal Gridless Recovery

Abstract

Multiple-input multiple-output (MIMO) array synthetic aperture radar (SAR) can be used to directly obtain the 3-D imagery of the illuminated scene with a single track. Due to the length limitations of synthetic aperture and antenna array, the super-resolution algorithms within the framework of 2-D compressive sensing (CS) have been conceived to reconstruct the azimuth-cross-track plane image because of its spatial sparsity. Since the desired scatterers are presupposed to be distributed over a series of fixed grid points, the location accuracy of the existing 2-D CS algorithms is relatively low. To overcome this problem, a fast 2-D gridless recovery (GLR) algorithm for the 2-D imaging signal model established in the real domain is proposed in this paper. Extensive simulation results validate that the proposed 2-D real-valued gridless recovery approach can approximately improve the computational efficiency by a factor of ten in terms of CPU time when compared with that of the 2-D GLR algorithm in the complex domain.