传统测量手段监测矿区开采沉陷时所需的成本较高，且无法全面反映地表移动盆地的沉降情况。为了使矿区地表沉陷监测更全面高效，从而获得更高精度的概率积分预计参数，以内蒙古某矿区为例，先采用SBAS-InSAR技术处理27景Sentinel-1A卫星数据，获得2017年9月至2018年7月间的全矿区地表时序形变情况，再结合改进步长的果蝇优化算法实现地表全盆地3 723个点的共同求参。结果显示，工作面开采导致的地表最大沉降值为201 mm，与实测数据相比，其绝对误差的平均值为3.48 mm，标准差为51.16 mm，均方根误差为10.64 mm。研究结果表明：SBAS-InSAR技术与传统手段相比，对于监测矿区工作面开采引起的地表全盆地沉陷具有较大优势；此外，采用改进步长的果蝇优化算法能将全盆地开采沉陷结果用于概率积分预计参数的求取，得到一组效果良好的参数；获得的研究区域最优概率积分预计参数为：下沉系数q=0.33，主要影响角正切tanβ=1.83，拐点偏移距s=0.045H，开采影响传播角θ0=89°。研究成果为今后矿区地表的开采沉陷监测与概率积分预计参数确定提供了科学依据。

The cost of traditional measurement method to monitor mining subsidence is high, and always can not reflect the subsidence of the whole basin. So in order to monitor mining subsidence more comprehensively and efficiently, and determine the optimal probability integral prediction parameters, taking a mining area in Inner Mongolia as an example, the authors used SBAS-InSAR technology to process 27 Sentinel-1A data, and obtained the surface time series deformation of thewhole mining area from September 2017 to July 2018. Then, combined with the fruit fly optimization algorithm, 3 723 points in the whole basin were jointly calculated the optimal probability integral prediction parameters. The monitoring results show that the maximum surface subsidence caused by mining is 201 mm. Compared with the measured data, the average absolute error is 3.48mm, the standard deviation is 51.16 mm, and the root mean square error is 10.64 mm. It can be seen from the research that SBAS-InSAR technology can well monitor the whole basin deformation of the mining face. Besides,the fruit fly optimization algorithm can apply the mining subsidence results of the whole basin to the calculation of probability integral prediction parameters, and obtain a set of parameters with good effect. The predicted parameters of probability integral method are q=0.33,tan β=1.83,s=0.045H, θ0=89°.The research results provide a scientific basis for mining subsidence monitoring and parameter calculation of the whole basin