星载斜视滑动聚束SAR子孔径成像处理算法研究

斜视滑动聚束大幅提升了星载SAR单航过多角度观测能力和观测灵活性，但随着斜视角和扫描角度增加，斜视附加带宽和非线性变化的瞬时多普勒中心给多普勒解混叠带来困难。针对上述问题，本文提出了一种基于子孔径处理的星载斜视滑动聚束成像算法。该算法首先改进了传统子孔径划分方法，通过两维频谱拼接和多普勒滤波，解决了子孔径数据仍存在的多普勒混叠，然后利用基于四阶斜距模型的CS算法完成聚焦成像。最后，通过计算机仿真验证了方法的有效性。 

Processing of Spaceborne Squint Sliding Spotlight SAR Data with Sub-aperture Data Division

Squint sliding spotlight improves the multi-angle imaging capacity with the single pass and the imaging flexibility of spaceborne synthetic aperture radar (SAR). However, with the increase of the squint angle and the beam scanning angle in azimuth, it is difficult to solve Doppler aliasing caused by the additional bandwidth owing to the squint angle and the nonlinear instantaneous Doppler centroid. In this paper, a new spaceborne squint sliding spotlight imaging algorithm based on sub-aperture data preprocessing is proposed to solve this problem. The traditional sub-aperture data partitioning method is modified, and the remained Doppler aliasing in each block of sub-aperture data is resolved by two-dimensional spectrum mosaic and Doppler filtering. Afterwards, the refined chirp scaling (CS) algorithm based on the fourth-order slant distance model is adopted for SAR data focusing imaging. Finally, the proposed imaging algorithm is validated by simulation results.