| Underground coal fire is a common natural environmental phenomenon in many coal fields,and its monitoring,evaluation,and management have received extensive attention.In order to make full use of the advantages of InSAR's large-scale monitoring of surface subsidence to identify coal fire areas,overcome the disadvantages of traditional time-series InSAR monitoring in coal fire areas,and fully excavate the information contained in the SAR data.This paper proposes a distributed scatterer phase optimization method of DSInSAR technology based on the principal component analysis,which is applied to the surface deformation monitoring of the the Fukang coal fire area in Xinjiang,and the settlement monitoring results of the fire area are compared with the measured coal fire points for analysis.The main work and research results of this paper are as follows:(1)The principle of InSAR height measurement and the principle of D-InSAR monitoring of subsidence are systematically explained,and the limitations of D-InSAR are discussed.This leads to introduces the PS-InSAR technology with single master image and SBAS-InSAR technology with the multi master image.Taking the above two timeseries InSAR methods in the coal fire area with insufficient monitoring point density as an opportunity,this paper introduces the current commonly used DS-InSAR technology that uses the information of distributed scatterers to increase the distribution density of monitoring points.(2)This thesis analyzes and shows that the key steps of the current DS-InSAR technology are divided into two steps,one is homogeneous pixel identification,and the other is to carry out phase optimization of distributed scatterer targets.Then,several existing hypothesis testing methods for homogenous pixel identification are introduced in detail,and rely on real SAR data to obtain the identification results of each method,and select typical feature types to perform a simple comparative analysis of the identification results;A method for optimizing the phase of distributed scatterers based on singular value decomposition and principal component analysis is proposed.A simulation method of time series interferogram is introduced.The reliability and effectiveness of the proposed method are quantitatively and qualitatively analyzed using simulation data.Meanwhile,real SAR data are used to carry out settlement monitoring in the experimental study area based on the proposed method,in which three quantitative indicators are used to analyze the quality of the optimized interferogram.The monitoring results show that the proposed method can greatly increase the number and distribution density of monitoring points,and the settlement area of the test area is counted.The settlement area that monitored by the proposed method is also significantly improved.(3)The traditional PS-InSAR technology,the DS-InSAR technology under the weighted average optimized interferogram and the DS-InSAR technology under the proposed method to optimize the interferogram are used to monitor the surface deformation of Xinjiang coal fire area.The monitoring results show that the proposed DS-InSAR technology can greatly increasing the number and distribution density of surface subsidence monitoring points in coal fire area,making the characteristics of surface subsidence caused by coal fire more intuitive and obvious.The results are superimposed and analyzed with known coal fire points to obtain the validity and reliability of the monitoring results,which further confirms the feasibility of identifying coal fire burning areas by monitoring ground subsidence.The settlement center time series settlement map and section settlement map of the Laobatai fire area and the Wugonggou fire area are drawn in the key subsidence areas of the Fukang coal fire area,then the subsidence characteristics are analyzed and find that the surface subsidence caused by the coal fire may have multiple subsidences funnel.There are 33 figures,8 tables,and 89 references... |
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