基于压缩感知的下视三维合成孔径雷达(DL 3D SAR)成像算法可以采用低于Nyquist采样率的采样数据实现平台正下方的高分辨成像。但是已有的算法在跨航向重构时采用的大都是单测量向量(SMV)模型,存在重构耗时长、受噪声干扰大的缺点。从单测量向量的推广形式即多重测量向量(MMV)模型出发,将DL 3D SAR中的跨航向处理与沿航迹向处理顺序交换,利用多重测量向量恢复具有相同稀疏结构的跨航向信号,提出了一种基于MMV模型的DL 3D SAR成像算法。相比于SMV模型的DL 3D SAR成像算法,该算法在运算时间、抗噪性能及重构精度方面均有所提高,并通过仿真实验验证了算法的有效性。

The downward-looking three-dimensional synthetic aperture radar (DL 3D SAR) imaging method based on compressed sensing could complete the high-resolution imaging by using the sampling data below the Nyquist sampling rate. However, the existing DL 3D SAR imaging methods which used for cross-track profile reconstruction are based on the single measurement vectors (SMV) model and has defects of time-consuming and noise-affected. Based on the multiple measurement vectors (MMV) model, the order of cross-track and along-track in the DL 3D SAR imaging process are exchanged. By using the same sparse structure in cross-track domain for different along-track measurements, the DL 3D SAR imaging method based on MMV model is proposed. The proposed method is superior to the SMV-based method both on time-consuming, reconstruction accuracy and anti-noise performance, and the effectiveness is verified by the simulation experiments.