基于压缩感知的宽孔径SAR成像

宽孔径SAR数据包含目标不同姿态角散射信息,实现宽孔径SAR成像对目标轮廓重构与解译识别具有重要价值.本文首先提出点模糊函数(point ambiguous function,PAF)研究影响压缩感知SAR成像的因素,然后用模型失配函数(model mismatch fucntion,MMF)分析宽孔径测量条件下点散射模型失配对成像性能的影响.最后根据上述结论,选择发射信号参数改善测量矩阵性能,利用广义似然比检验方法克服模型失配对成像性能的影响.实验结果验证了本文结论的正确性和成像算法的有效性.

Wide aperture SAR imaging based on compressive sensing

The wide aperture SAR collect object signature from different aspects, which means that wide aper- ture SAR imaging is valuable for object visualization and automatic target recognition （ATR）. In this paper, the point ambiguous function （PAF） is proposed to analyze the factors which dominate the performance of com- pressed SAR imaging. Then the model mismatch function （MMF） is presented to study the instability which is the result of the mismatch of point scattering model assumption for wide aperture SAR. By these analyses, the Gaussian white noise waveform is applied for improving the performance of PAF, and generalized likehood ratio test method is applied to relieve the instability of imaging which is caused by model mismatch. Experiments results validate the effectiveness of PAF and MMF, and the feasibility of proposed algorithm.