低信噪比下基于Hough变换的前视阵列SAR稀疏三维成像

Sparse Three-dimensional Imaging Based on Hough Transform for Forward-looking Array SAR in Low SNR

低信噪比下压缩感知稀疏重构的性能不佳,使得前视阵列SAR稀疏3维成像的质量大大降低。为此,该文结合散射系数矢量在原始的距离向和斜距离向2维空间中的连续性特征,借鉴信号检测中常用的直线检测思路和方法,提出基于霍夫变换的压缩感知稀疏重构算法,有效提高压缩感知稀疏重构的性能。同时,仿真实验结果表明,该方法有效实现了低信噪比下前视阵列SAR的稀疏3维成像。

The performance of sparse reconstruction algorithm of compressive sensing in low Signal-to-Noise Ratio （SNR） is lower, and the quality of sparse three-dimensional imaging for forward-looking array synthetic aperture radar in low SNR is reduced greatly. To solve this problem, a validate method of reconstruction algorithm of compressive sensing based on Hough transform is proposed, in which the continuity of the scattering coefficient vector in the two-dimensional space of range direction and slant range direction and the straight line detection method of Hough transform is used, and thus the reconstruction quality of compressive sensing is increased effectively. Also, the simulation experiments indicate that this method can improve the sparse three-dimensional imaging for forward-looking array SAR in low SNR effectively.