面向矿区地表形变的GPS-InSAR融合方法研究

Research on Surface Deformation Monitoring in Mining Areas Based on GPS-InSAR Fusion Method

煤炭资源高强度的开发与利用容易导致开采沉陷,威胁矿区安全生产。多源监测数据融合是实现矿区地表形变高效监测的关键手段。针对GPS与InSAR技术在地表形变监测时存在的不足,提出一种融合GPS与InSAR数据的遗传-克里金插值方法对矿区地表形变进行监测。融合GPS与InSAR数据进行克里金插值,寻找最佳变异函数模型计算研究区的年平均形变速率;随后通过遗传算法对变异函数模型的参数进行寻优,进一步提高插值模型的精度;最后以GPS站点的实测数据,对模型的性能进行验证和评价。结果表明:融合GPS数据的遗传-克里金插值算法可有效提高地表形变监测的精度。研究成果有望提高地表形变监测的效率,对矿山地质灾害防治与地面保护工作具有一定的参考价值。

The high intensity development and utilization of coal resources can easily lead to mining subsidence and threaten the safety of production in mining areas.Multi source monitoring data fusion is a key means to achieve efficient monitoring of surface deformation in mining areas.Aiming at the shortcomings of GPS and Interferometric Synthetic Aperture Radar(InSAR)techniques in monitoring surface deformation,a genetic Kriging interpolation method integrating GPS and InSAR data is proposed to monitor surface deformation in mining areas.Combining GPS and InSAR data for Kriging interpolation,searching for the best variogram model to calculate the annual average deformation rate in the study area;Subsequently,genetic algorithms are used to optimize the parameters of the mutation function model to further improve the accuracy of the interpolation model;Finally,the performance of the model is verified and evaluated using measured data from GPS stations.