Research On InSAR Filtering Algorithm For Mining Subsidence Monitoring

In order to make rational use of mineral resources and respond to national policies,the mining mode of mineral resources has been constantly transformed,and the environmental management of mining areas has attracted much attention,the mine disaster early warning system has been constantly upgraded and improved,In recent years.As a rapidly developing measurement method,synthetic aperture radar interferometry(InSAR)has the advantages of all-weather,planar,wide range and saving manpower and financial resources.In this paper,InSAR technology is used to monitor surface deformation near railway in mining area.This paper mainly focuses on the application of InSAR in surface monitoring of mining area and the improvement of interference image denoising technology in mining area.In this paper,the Non-Local means filter(NL-means)method is applied to filter InSAR interferograms in mountain mining areas,which can better retain the phase information of the interferograms while eliminating the noise of the InSAR interferograms,and is conducive to the further research work.The main research results are as follows:(1)The accuracy requirement of auxiliary DEM of InSAR technology applied to surface monitoring in mountain mines is analyzed experimentally.The results show that GTOP 30 DEM of 900m*900m resolution is less applicable in complex mountain areas,SRTM V3 DEM of 30m*30m resolution is more applicable,and DEM data of 10m*10m resolution is better.Auxiliary DEM data with resolution not less than 30m*30m is recommended as external reference data for InSAR processing.(2)Non-Local Means algorithm is introduced into InSAR interferogram filtering,and the traditional Non-Local Means filtering is improved by using InSAR-specific coherent images,so that it can adjust the filter smoothing factor adaptively in InSAR interferogram,eliminate speckle noise in different noise areas to varying degrees,and retain the true value of the image.Through the interference images with different noise densities,the improved filtering algorithm is compared with the traditional algorithm.The results show that the improved filtering algorithm is superior to the traditional interferogram filtering method,especially in the area of excessive noise density,the filtering effect is better.(3)Applying the improved filtering algorithm to the InSAR technical process,the subsidence and boundary movement caused by mining in 1309 working face of a mining area are monitored.The results show that the subsidence trend monitored by InSAR technology is basically consistent with the measured data,but the accuracy,especially in the central area of the working face,is low.(4)In view of the insufficiency of InSAR technology in monitoring surface subsidence in long time series,small baseline set technology is used to monitor and analyze surface subsidence in mining area.Compared with D-InSAR technology,SBAS technology improves the time resolution and image utilization rate of InSAR monitoring,and is more sensitive to surface deformation.Therefore,the monitoring result of SBAS method is better than D-InSAR in theory and works in mine 1309.In the application of this method,the monitoring results of SBAS are consistent with the theory,and the absolute error of the monitoring results of SBAS method is 7.5mm compared with the measured data.