This article presents a new scheme called 2-D mixed compressive sensing back-projection (CS-BP-2D), for synthetic aperture radar (SAR) imaging on a geocoded grid, in a single measurement vector frame. The back-projection linear operator is derived in matrix form and a patched-based approach is proposed for reducing the dimensions of the dictionary. Spatial compressibility of the radar image is exploited by constructing the sparsity basis using the back-projection focusing framework and fast solving the reconstruction problem through the orthogonal matching pursuit algorithm. An artifact reduction filter inspired by the synthetic point spread function is used in postprocessing. The results are validated for simulated and real-world SAR data. Sentinel-1 C-band raw data in both monostatic and space-borne transmitter/stationary receiver bistatic configurations are tested. We show that CS-BP-2D can focus both monostatic and bistatic SAR images, using fewer measurements than the classical approach, while preserving the amplitude, the phase, and the position of the targets. Furthermore, the SAR image quality is enhanced and also the storage burden is reduced by storing only the recovered complex-valued points and their corresponding locations.

中文翻译：

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基于地理编码网格的SAR混合压缩感知反投影

本文提出了一种称为二维混合压缩感测反投影（CS-BP-2D）的新方案，用于在单个测量矢量帧中在地理编码网格上合成孔径雷达（SAR）成像。反投影线性算子以矩阵形式导出，并提出了一种基于补丁的方法来减小字典的维数。雷达图像的空间可压缩性是通过使用反投影聚焦框架构造稀疏性基础，并通过正交匹配追踪算法快速解决重建问题而实现的。后处理中使用了受合成点扩展功能启发的伪影减少滤波器。结果已针对模拟和真实SAR数据进行了验证。测试了单静态和星载发射机/固定接收机双基地配置中的Sentinel-1 C波段原始数据。我们表明，CS-BP-2D可以聚焦比传统方法更少的测量，同时可以保留单幅和双静态SAR图像，同时保留目标的幅度，相位和位置。此外，通过仅存储恢复的复数值点及其对应位置，可以提高SAR图像质量，并减轻存储负担。