利用稀疏非负矩阵分解的大转角SAR成像方法

Wide angle SAR imaging via sparse non-negative matrix factorization

提出了一种采用稀疏非负矩阵分解(NMF)的大转角成像方法.首先将全孔径划分为若干相互重叠的子孔径,然后分别使用极坐标格式算法获得不同视角下的子图像,最终采用加入稀疏增强正则项的NMF算法在图像域对子图像进行迭代融合,获得目标增强和信噪比更高的全孔径综合图像.仿真实验结果验证了该方法的有效性.

This paper proposes a novel WASAR imaging scheme , which divides the full aperture data into several overlapping sub-apertures and uses the Polar Format Algorithm （ PFA ） to obtain sub-images at different aspects . Finally we perform full aperture image composition via Non-negative Matrix Factorization （ NMF） with a sparse regularization term . The target feature of the synthesized image is enhanced and the SNR is improved . Simulation results verify the effectiveness of the novel approach .