基于D-InSAR和概率积分法的矿区大变形地表沉降提取方法

摘要

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%)。%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%).