深基坑工程在施工管理阶段的形变破坏是一个非常复杂的过程，往往由局部支护结构破坏或土体失稳引起，导致大范围倒塌，后果非常严重。本课题试图融合基坑监测多传感器与地基SAR数据，获取高精度三维形变，智能反演与预警深基坑形变破坏的发生发展。主要研究GB-SAR影像精密配准和大气相位滤波分离技术，研究非连续地基SAR监测的“轨道”重定位误差改正与高相干点提取，重点研究多源数据融合理论与三维形变监测数据约束的GB-SAR相位解缠，建立高精度深基坑监测、模拟、反演与预警模型，优化基坑形变破坏的力学机制与内部结构参数，构建网络化智能监测预警管理系统，为安全管理与施工组织再优化提供理论基础；对推动深基坑形变监测理论与发展，揭示其形变破坏机理等方面具有重要的学术价值和现实意义。

Deformation damage of deep foundation pits is a very complex process during the construction management stage, it is often caused by the failure of part support structures or soil instability, and leads to large-scale collapse with serious consequences. This project attempts to integrate both multi-sensor and ground-based SAR data for foundation pit monitoring, to obtain high precision three-dimensional deformation, intelligent inversion and early warning of the occurrence of deep foundation pit deformation and damage. To do this, we need to: study the precision registration of GB-SAR images and atmospheric phase filtering separation technology, correcting the ‘orbital’ relocation errors, extract high coherence point of discontinuous ground-based SAR monitoring, and focus on multi-sources data fusion theory and GB-SAR phase unwrapping based on three-dimensional deformation monitoring data constraints. The establishment of high precision monitoring, simulation, inversion and early warning model would optimize the deformation mechanics and internal structural parameters of the deep foundation pit. In addition to building a network intelligent monitoring and early warning management system about the deep foundation pit, and providing a theoretical basis for safety management and more scientific construction organization. This has an important academic value and practical significance, in promoting deep foundation pit deformation monitoring theory and its development, and in revealing the deformation and damage mechanism of deep foundation pit.