CAJ | 학술논문

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。
위료정학지대대면적광구진행침강감측，이주위IGS근종참위삼고점，건립고정도위성도항계통(GNSS)변형감측망。감우IGS근종참적비선성운동，결합속도장신식급주해좌표，급출항차잡이만려파모형(RKF)，병용우학정IGS근종참불동역원대응적좌표기준。통과환북광구침강감측실례대해방법진행험증。결과표명：RKF모형학정적좌표기준우우예측모형급IGS분석중심제공적주해좌표；당관측시간대우4 h시，대응적감측정도가이체도호미급。해방법가이고효、준학지감측대면적광구침강。
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.