The Same Range Line Cells Based Fast Two-Dimensional Compressive Sensing For Airborne MIMO Array SAR 3-D Imaging

Abstract

Airborne multiple-input multiple-output array synthetic aperture radar (MIMO array SAR) can be used to directly obtain the three-dimensional (3-D) imagery of the illuminated region with a single track. Different sparse reconstruction algorithms within the framework of compressive sensing (CS) have been conceived to reconstruct the cross-track signal because of its inherent spatial sparsity. However, the computational complexity and the number of two-dimensional (2-D) SAR images needed for sparse reconstruction of the existing algorithms are usually high. To overcome this problem, the same range line cells based 2-D real-valued CS is proposed in this paper. In this new algorithm, the original signal model is transformed from the complex domain to the real domain by means of unitary transformation. Finally, airborne MIMO array SAR real experimental results are illustrated to validate the prominent advantages of the proposed method.