基于频域稀疏压缩感知的星载SAR稀疏重航过3维成像

星载合成孔径雷达(SAR)稀疏重航过3维成像技术通过交轨向的多次飞行观测，获得观测场景的第3维分辨。该文给出了单颗卫星SAR稀疏重航过轨道分布，为有效缩短重访时间，同时给出了编队双星SAR轨道分布，对应的交轨向等效孔径长度为20 km。提出了一种基于干涉处理和频域压缩感知(CS)的稀疏3维成像方法，利用稀疏重航过中的部分回波形成参考3维复图像，对待重建SAR 3维图像信号进行干涉处理，使信号在频域具备稀疏性。在大轨道分布范围下，建立频域距离向-交轨向线性测量矩阵，利用CS理论联合求解稀疏表征下的图像频谱，避免交轨向和距离向的回波信号耦合。将求解所得频谱逆变换至空间域，可得到观测场景的3维图像重建结果。仿真结果表明，该文方法在稀疏采样率74.4%条件下，仍可获得与满采样成像性能相当的结果，验证了干涉处理频域稀疏方法在星载SAR 3维成像中的有效性。

Sparse Flight 3-D Imaging of Spaceborne SAR Based on Frequency Domain Sparse Compressed Sensing

The space-borne Synthetic Aperture Radar (SAR) sparse flight three-dimensional (3-D) imaging technology through the multiple observations in cross-track direction obtains the 3-D spatial distribution of the observed scene. In this paper, the orbit distribution of single satellite SAR sparse flight is given. In order to shorten effectively the satellite revisit time, the formation of double star SAR orbit distribution is given. The corresponding cross-track equivalent aperture length is 20 km. A sparse 3-D imaging method based on interferometry and compressed sensing is proposed. The referential complex image is formed by using part of the echoes of the sparse flight, and the SAR 3-D image signals which are to be reconstruct are processed by interferometry. This method makes the signal sparse in the frequency domain. Under the large orbit distribution range, the frequency domain range direction and cross-track linear measurement matrix is established, which is beneficial to the Compressed Sensing(CS) theory to solve jointly the image frequency spectrum under sparse representation, and avoid the echoes coupling between the range and cross-track direction. Inversely transforming the resulting spectrum into the spatial domain, the reconstruction result can be obtained. Simulation results show that under the condition of sparse sampling rate of 74.4%, the imaging  performance of the proposed method is still comparable to that of full sampling.