基于压缩感知的连续场景稀疏阵列SAR三维成像

该文提出一种基于压缩感知的连续场景稀疏阵列SAR 3维成像方法。利用多孔径观测结构，使SAR复图像在频域和变换域具备稀疏性，将压缩感知(CS)方法引入频域和变换域的信号处理过程中，实现高分辨率3维成像，获得与满阵成像结果相同的成像质量。该文方法适用于随机稀疏阵列，可减少对高程向阵型的设计约束，为孔径综合处理后无法获得满阵条件下实现对地成像提供了可能。仿真试验验证了该文方法的有效性。

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.