Sparse Array SAR 3D Imaging for Continuous Scene Based on Compressed Sensing

In this paper a sparse array SAR 3D imaging for continuous scene based on Compressed Sensing (CS) is proposed. It exploits the sparsity property of the SAR image under multi-aperture observation structure which supposes that SAR images become sparse in the transform domain by eliminating the random phase of each scattering cell, and CS theory is introduced into the signal processing in the transform domain. The proposed method can achieve high resolution 3D imaging and get nearly the same image quality as the full array with a few samplings. The proposed method decreases the constrain of the array designing on elevation direction and provides the possibility for imaging in the situation that a full equivalent array cannot be achieved. Simulation results verify the effectiveness of the proposed method.