基于IGS跟踪站的大面积矿区GNSS变形监测

摘要

In order to monitor large-area mining subsidence accurately, a high-precision global navigation satellite system (GNSS) monitoring network was established based on the nearby international GNSS service (IGS) stations taken as reference points. Given the non-linear motions of IGS stations, the robust Kalman filtering (RKF) model was presented to determine the datum of multi-period monitoring network considering the velocity and weekly solution of IGS stations. The theory proposed was applied to monitoring mining subsidence in northern Anhui coal mine in China. According to the case study, the RKF model to establish monitoring datum is better than the prediction method and the weekly solution from IGS analysis centers (ACs), and the corresponding precision of deformation can reach up to millimeter level with 4 h observation. The research provides an efficient and accurate approach for monitoring large-area mining subsidence.%为了精确地对大面积矿区进行沉降监测，以周围IGS跟踪站为参考点，建立高精度卫星导航系统(GNSS)变形监测网。鉴于IGS跟踪站的非线性运动，结合速度场信息及周解坐标，给出抗差卡尔曼滤波模型(RKF)，并用于确定IGS跟踪站不同历元对应的坐标基准。通过皖北矿区沉降监测实例对该方法进行验证。结果表明：RKF模型确定的坐标基准优于预测模型及IGS分析中心提供的周解坐标；当观测时间大于4 h时，对应的监测精度可以达到毫米级。该方法可以高效、准确地监测大面积矿区沉降。