【摘要】 随着合成孔径雷达（synthetic aperture radar,SAR）影像的持续积累，合成孔径雷达干涉测量（interferometric synthetic aperture radar,InSAR）技术在处理广域长时序地表形变监测任务时，面临数量激增带来的计算瓶颈。尤其是采用分布式散射体InSAR(distributed scatterers InSAR,DS-InSAR)方法时，干涉对的全组合策略导致解算过程极为耗时，限制了其在大区域形变监测中的广泛应用。由于时序InSAR数据在时空维度上通常包含大量冗余信息，影像压缩成为去除冗余信息的有效解决手段。因此提出一种基于张量分解的广域长时序InSAR影像压缩方法，利用空间内像素统计特性的一致性将协方差矩阵重构为三阶张量，并借助Tucker分解实现时空维数据压缩。为验证其有效性，选取昆明市主城区Sentinel-1A影像进行实验。结果显示，在2×3和2×5的子空间窗口设置下，处理效率分别提高约24倍与40倍，且形变反演精度仍符合监测要求；当子空间窗口为2×10和2×15时，尽管部分信息丢失，主要形变区域依然可辨识，此时效率提升分别达约80倍与120倍。为应对广域长时序InSAR形变监测中的计算难题提供了一种新的途径，具有较好的工程应用前景。更多还原

【Abstract】 Objectives: With the continuous accumulation of synthetic aperture radar(SAR) images, interferometric synthetic aperture radar(InSAR) technology is facing a computational bottleneck caused by the surge in the number of SAR images when processing wide area and long-term surface deformation monitoring tasks. Especially for the distributed scatterers InSAR(DS InSAR) method, the full combination strategy of interferometric pairs results in an extremely time-consuming solution process, limiting its widespread application in large-scale deformation monitoring. However, temporal InSAR data often contains a large amount of redundant information in the spatiotemporal dimension. Removing redundant information through image compression has become an effective solution. Methods: This paper proposes a tensor decomposition-based method for wide area long time series InSAR image compression. The proposed method utilizes the consistency of spatial pixel statistical properties to reconstruct the covariance matrix into a thirdorder tensor, and uses Tucker decomposition to achieve spatiotemporal data compression. Results: To verify its effectiveness, Sentinel-1A images from the main urban area of Kunming city are selected for the experiment. The results show that under the compression subspace settings of 2×3 and 2×5, the processing efficiency is improved by about 24 times and 40 times, respectively, and the deformation inversion accuracy still meets the monitoring requirement. When the subspace is expanded to 2×10 and 2×15, although some information is lost, the main deformation area can still be identified, and the efficiency is improved by about 80 times and 120 times, respectively. Conclusions: This paper provides a new approach to address the computational challenges in wide area long-term InSAR deformation monitoring, and has good engineering application prospects.更多还原