| At present,coal energy still occupies an important position in China’s energy structure and plays a leading role in social and economic development.However,the mining of coal resources will destroy the surface and buildings around the mining area,and even endanger the safety of people’s lives and property.Therefore,it is of great significance to conduct long-time(more than 6 years)and high-precision surface subsidence monitoring and early warning for mining area.Taking Zhaojiazhai and Wangxingzhuang coal mines in Xinzheng City,Henan Province and Zhouyuanshan coal mine in Zixing City,Hunan Province as the main research objects,the paper uses InSAR time-series SAR image compression algorithm to monitor the surface deformation of mining areas for a long time.The main work contents and results are as follows:(1)The paper expounds the basic working principle of DS-InSAR technology.Two groups of Sentinel-1A images covering Zhaojiazhai coal mine and Wangxingzhuang coal mine in Xinzheng City from January to December 2021 are used as data sources.The surface deformation information of the two mining areas is obtained by processing SAR images through DS-InSAR technology,and the monitoring results of the two groups of images are compared and verified.The experimental results show that DS-InSAR technology effectively improves the coherence point density of surface deformation in the mining area,obtains the effective information of surface deformation in the mining area,and the standard deviation of the two groups of image monitoring results is only 0.86 mm,which proves that DS-InSAR technology is feasible and suitable for monitoring surface deformation in mining area.(2)In view of the long-term(more than 6 years)monitoring of surface deformation in mining areas,using InSAR technology to monitor mining areas is faced with problems such as insufficient spatial density of coherent targets,aggravation of decoherence effect in mining areas and low calculation efficiency,We propose a time dimension reduction compression processing algorithm is proposed.The main steps are to construct covariance matrix,phase compensation and dimension reduction reconstruction.Through feature extraction of each group of images,The phase linking algorithm is used to compensate the phase of the auxiliary image,and the eigenvector corresponding to the maximum eigenvalue of the covariance matrix is selected to obtain the virtual image.Since the number of virtual images is far less than the number of original images,the virtual image is processed in time sequence,which greatly improves the spatial density of coherent targets in the mining area,image coherence and SAR image processing efficiency.(3)The time dimension reduction compression processing method of time series SAR image is applied to the monitoring of surface subsidence of Zhouyuanshan coal mine in Zixing City,Hunan Province.The sentinel-1A orbit lifting image data covering Zhouyuanshan coal mine from June 2015 to August 2021 is used as the data source.The image data of the mining area is processed by DS-InSAR technology and dimension reduction compression algorithm,and compared with the measured level data of the mining area,The experimental results show that the interferogram processed by virtual image differential interferometry has high signal-to-noise ratio,more coherent point targets,and the processing efficiency is improved by more than 90%.In addition,the deformation results of PS points along the strike and dip of the mining area are basically consistent with the variation trend of leveling data results,which proves the reliability of time-series SAR image compression algorithm applied to long-term monitoring of surface subsidence in mining area,It is considered that this method is a better choice for surface deformation monitoring under the background of long-term(more than 6 years)big data in mining area. |
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