A model for extracting large deformation mining subsidence using D-InSAR technique and probability integral method  

基于D-InSAR和概率积分法的矿区大变形地表沉降提取方法(英文)

作　　者：范洪冬[1,2] 顾伟[1] 秦勇[2] 薛继群 陈炳乾[1] 

机构地区：[1]中国矿业大学江苏省资源环境信息工程重点实验室,徐州221116 [2]中国矿业大学资源与地球科学学院,徐州221116 [3]中化地质矿山总局浙江地质勘查院,杭州310002

出　　处：《Transactions of Nonferrous Metals Society of China》2014年第4期1242-1247,共6页中国有色金属学报（英文版）

基　　金：Project (BK20130174) supported by the Basic Research Project of Jiangsu Province (Natural Science Foundation) ;Project (1101109C) supported by Jiangsu Planned Projects for Postdoctoral Research Funds,China;Project (201325) supported by the Key Laboratory of Geo-informatics of State Bureau of Surveying and Mapping,China;Project (SZBF2011-6-B35) supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions,China

摘　　要：Due to the difficulties in obtaining large deformation mining subsidence using differential Interferometric Synthetic Aperture Radar （D-InSAR） alone, a new algorithm was proposed to extract large deformation mining subsidence using D-InSAR technique and probability integral method. The details of the algorithm are as follows：the control points set, containing correct phase unwrapping points on the subsidence basin edge generated by D-InSAR and several observation points （near the maximum subsidence and inflection points）, was established at first; genetic algorithm （GA） was then used to optimize the parameters of probability integral method; at last, the surface subsidence was deduced according to the optimum parameters. The results of the experiment in Huaibei mining area, China, show that the presented method can generate the correct mining subsidence basin with a few surface observations, and the relative error of maximum subsidence point is about 8.3%, which is much better than that of conventional D-InSAR （relative error is 68.0%）.针对差分合成孔径雷达干涉测量(D-InSAR)技术无法正确获取矿区地表大沉降量的问题,提出D-InSAR及概率积分法联合获取矿区沉降量的新方法。具体过程为:由D-InSAR技术得到下沉盆地,选取盆地边缘相干系数较大而下沉量较小的点,再加入最大下沉点和拐点附近的少量实测点作为解算控制点;然后采用遗传算法对概率积分法参数不断进行优化;最后,由解算的最优参数反算地表下沉盆地。实例表明,该方法能够在减少地面监测点数量的情况下获取较为准确的地表沉降场,最大下沉的相对误差为8.3%,优于D-InSAR的监测结果(相对误差约68.0%)。

关 键 词：D-INSAR genetic algorithm probability integral method mining subsidence 

分 类 号：P642.26[天文地球—工程地质学]