~随着我国经济的快速发展，人们对煤炭的需求不断扩大，煤炭开采是获取能源的主要方式，我国煤炭开采以地下开采为主，通过地下巷道系统将地层中的煤炭运输到地面。众所周知，煤炭开采会造成煤层上覆岩层的塌陷，从而对地形地貌及地面建筑物造成破坏。因此，对地表岩体在煤炭开采过程中发生的位移和形变的监测和研究迫在眉睫。
InSAR技术有其独特的技术优势，能够全天时、全天候且实现大范围的地表形变的高精度监测。InSAR技术相对于传统观测技术而言，空间分辨率高、监测精度高，而且InSAR技术具有传统监测技术所不具备的大范围监测能力。SAR影像可以根据卫星的重访周期进行重复观测，从而达到高效率实时动态监测。InSAR技术可以弥补人工外业测量的安全性问题，同时节省了人力、物力和财力。
本文以SBAS-InSAR技术监测煤矿区沉降的方法为研究重点。针对SBAS-InSAR技术选择地面控制点（GCP）受人为主观因素影像大的问题，将PS-InSAR技术中所得到的PS点通过筛选作为SBAS-InSAR的地面控制点（GCP）以改进SBAS-InSAR技术，并对三种InSAR技术的监测结果进行交叉对比，最后采用SSA-BP算法建立了矿区开采沉陷预测模型。论文主要研究成果如下：
（1）探讨了InSAR技术的几何原理和SBAS-InSAR、PS-InSAR技术的基本原理，并对两种技术进行了对比分析。
（2）以陕西省榆林市张家峁煤矿为例，采用21景C波段sentinel-1A数据，分别采用SBAS-InSAR技术、PS-InSAR技术和改进的SBAS-InSAR技术对数据进行处理，通过结果对比、实测数据比较两方面验证了结果的可靠性。
（3）利用地面水准观测点对SBAS-InSAR技术、PS-InSAR技术和改进的SBAS-InSAR技术结果进行精度验证，结果显示相关性较高。将获得的监测点累积形变量进行建模，实现煤矿采空沉陷区的三维重构。结果显示，研究区域内共有多处区域发生大量级沉降现象，其中北部区域沉陷状况最严重，最大沉降速率可达-146.76mm/a。
（4）提出了利用时序InSAR技术和SSA-BP算法建立煤矿开采沉陷预计模型，结合改进SBAS-InSAR技术监测得到的时序沉降量，在工作面走向和倾向上均匀选点，建立煤矿开采沉陷动态预计模型，并对预测结果进行了精度评定。
 

~With the rapid development of my country's economy，people's demand for energy continues to expand. Mining is the main way to obtain energy. Mineral mining is an underground operation，and the coal buried deep in the ground is transported to the ground through underground tunnels. Therefore，the safety of underground coal mines should continue to be studied in depth. As the excavation depth increases，the overlying strata of the coal seam collapse. Therefore，it is necessary to conduct deeper research on the underground operation of mining，and take effective measures to prevent the occurrence of subsidence. China's economy is developing rapidly， and the country's demand for energy is also rapidly increasing. Mining is the most important way to obtain energy. Most of the mining work is carried out underground，and the mineral resources buried deep in the ground are transported to the land through underground tunnels， which requires a sufficient understanding of the displacement and deformation of the underground rock mass mining process. Therefore，it is urgent to provide effective and safe measures for underground mining technology.
InSAR technology has all-day，all-weather observation and can achieve high-precision monitoring of large-scale surface deformation. Compared with traditional observation technology，InSAR technology has high spatial resolution and high monitoring accuracy， and InSAR technology has large-scale monitoring capabilities that traditional monitoring technology does not have. SAR images can be repeatedly observed according to the revisit cycle of the satellite， so as to achieve high-efficiency real-time dynamic monitoring. InSAR technology can make up for the safety of manual field measurement， while saving manpower， material and financial resources.
This paper focuses on the SBAS-In SAR technology to monitor the method of mining subsidence. Aiming at the problem that the selection of ground control points (GCP) in SBAS-In SAR technology is affected by the large image of human subjective factors， the PS points obtained in PS-InSAR technology are screened as the ground control points (GCP) of SBAS-InSAR to improve SBAS-InSAR technology，and cross-compared the monitoring results of the three -InSAR technologies， and finally established the SSA-BP algorithm to establish the mining subsidence prediction model in the mining area. The main research work includes:
(1) The geometric principle of In SAR technology is discussed，the basic principle of SBAS-In SAR technology and the basic principle of PS-InSAR technology are introduced， and the two technologies are compared and analyzed.
(2) Taking Zhangjiamao mining area in Yulin City，Shaanxi Province as the research area， using 21 scene C-band sentinel-1A data，using traditional SBAS-InSAR technology， traditional PS-In SAR technology， and improved SBAS-In SAR technology to process the data In order to achieve cross-validation， the reliability of the results is verified through the comparison of results and field conditions.
(3) The results of traditional SBAS-InSAR technology，traditional PS-InSAR technology， and improved SBAS-In SAR technology are used to verify the accuracy of ground level observation points， and the results show high correlation. The accumulated deformation variables of the monitoring points obtained are modeled to realize the three-dimensional reconstruction of the goaf subsidence area. The processing results show that there are many areas in the study area where massive subsidence occurs， among which the northern area is the most serious subsidence， and the maximum subsidence rate can reach -146.76mm/a.
(4) It is proposed to use the time series InSAR technology and the SSA-BP algorithm to establish a mining subsidence prediction model in the mining area. Combined with the time series subsidence monitored by the improved SBAS-In SAR technology， the points are uniformly selected in the direction and inclination of the working face， and the mining subsidence dynamic of the mining area is established. Predict the model and evaluate the accuracy of the prediction results.
 

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