Study On Monitoring Method Of Surface Subsidence In Filling Mining Area Based On DS-InSAR

As the "food for industry",coal is one of the three most important fossil fuels in the world today,and it is an indispensable basic energy source in the process of economic and social development.With the long-term large-scale mining of coal resources,the surface of the mining area has produced different degrees of subsidence problems.Surface subsidence in mining areas not only destroys the ecological environment,but also seriously affects the normal production and life of the people.Therefore,it is of great practical significance to carry out research on surface subsidence monitoring in mining areas.Due to the technical advantages of space-borne SAR system,such as all-weather,strong penetration ability and large monitoring range,the research of time-series InSAR method has been vigorously developed in the field of geodesy.On this basis,in this paper,the distributed target timing method of InSAR(DS-InSAR)for further study,and made some improvements in the process of data processing,rich technical system of the proposed method,at the same time in Jining filling mining area as the experimental area of the surface subsidence monitoring research,indicates the dynamic subsidence laws of the region.The main research work and results are as follows:(1)The theory and method of InSAR are summarized,and the basic principle and processing flow of PS-InSAR,Sta MPS and DS-InSAR are described respectively.In the DS-InSAR method,three commonly used homogeneous pixel selection algorithms,such as BWS test,KS test and HTCI,and eigenvalue decomposition of covariance matrix,are introduced in detail.(2)A dynamic confidence interval(D-HTCI)homogeneous pixel selection algorithm is proposed.Confidence interval hypothesis test algorithm(HTCI)as a homogeneous pixels,the selection of commonly used algorithms,this paper into Moravec operator in HTCI algorithm,based on the homogeneous pixels,the selection window pixels,the change of the mean intensity,dynamic control the size of confidence interval,and carries on the experiment using simulation and real data,proves the effectiveness of the proposed algorithm.(3)A phase optimization method combining non-local and Kalman filter is studied.Firstly,in the spatial non-local filtering,according to the amplitude deviation exponent of each pixel phase in the non-local estimation window,a model about the attenuation factor h in the normalized parameter is constructed,and the non-local filtering is selfadapted to improve the filtering quality.Then,on the basis of eigenvalue decomposition of covariance matrix and phase optimization of adaptive spatial non-local filtering,a phase optimization method is proposed.The Sentinel-1A images of 26 scenes covering a filling mining area in Jining from July 2018 to July 2019 were used as experimental data to analyze and evaluate each phase optimization method,which proved the feasibility and superiority of the improved and proposed method.(4)By selecting the 49 Sentinel-1A VV polarization images covering the filling mining area from September 17,2017 solstice to July 9,2019 as the experimental data,DS-InSAR method was used to carry out the application research related to the surface subsidence monitoring in different time periods.The results show that:(1)In the settlement monitoring experiments in each period,the DS-InSAR method significantly increases the number of final selected points,and obtains more detailed surface subsidence information,which is more helpful to the analysis of the temporal sequence subsidence law of the surface;(2)The atmospheric correction of the monitoring results in each period is carried out with the GACOS atmospheric correction model,which can better remove the influence of atmospheric delay on the monitoring results and improve the accuracy of the subsidence monitoring results and compared with the traditional Sta MPS,the DS-InSAR method has high precision and reliability;(3)Within the study area on 6300 and 2300 filling mining area for the surface subsidence in detail the results of analysis,combining with the actual mining working face in filling material,the results show that the filling mining area compared with better control of surface subsidence in the strip mining area,the surface subsidence magnitude smaller,basic architectural structures without damage,the study could be used to other filling mining area of wide area,long time monitoring surface subsidence.There are 55 figures,7 tables and 89 references.