基于迭代近端投影的二维欠采样合成孔径雷达成像

合成孔径成像雷达(SAR)具有数据量大、采样率高等特点，针对传统压缩感知(CS)的SAR成像存在精度低及抗噪性能差的问题，该文提出一种基于迭代近端投影(IPP)的2维欠采样合成孔径雷达成像重建方法。即通过对雷达回波构建为距离频域-方位多普勒域的2维稀疏表示模型，在此基础上将成像问题转化为距离向和方位向压缩感知稀疏重构问题，利用迭代近端投影算法的函数优化模型来表示合成孔径雷达成像中的稀疏表示，最后采用平滑削边绝对偏离(SCAD)罚函数获得近端算子以求解该模型并进行成像。仿真与实测数据处理结果表明，所提方法成像效果更好。

Two-dimensional Underwent Synthetic Aperture Radar Imaging Based on Iterative Proximal Projection

Synthetic Aperture Radar (SAR) imaging has a large amount of data volume, high sampling rate, and the problem of SAR imaging precision in traditional Compression Sensing (CS) is low, and there is a problem of poor anti-noise performance. A method of reconstruction method of two - dimensional sampling synthetic aperture rada based on Iterative Proximal Projection (IPP) is proposed. The radar echo is constructed as a two-dimensional sparse representation model in the range frequency-domain-azimuth Doppler region. On this basis, the two-dimensional imaging problem is transformed into the range and azimuth compression sensing sparse reconstruction. The function optimization model of the iterative proximal projection algorithm is used to represent the sparse representation of the synthetic aperture thunder imaging, and the proximal operator is finally obtained with the Smoothly Clipped Absolute Deviation (SCAD) penalty function to solve the model and to image. Simulation and measured data processing results show that the method of imaging is better.