Monitoring large-area mining subsidence by GNSS based on IGS stations

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.

On the Non-linear Motion of IGS Station

With the daily SINEX files of the IGS, the time series of IGS stations are obtained using an independently developed software under generalized network adjustment models with coordinate patterns. From the time series, non-linear motions are found. With spectral analysis method, the variation frequency （annual period and semi-annual period） of the site velocity is found. Moreover, the empirical model of the velocity variation of the station has been established by regression analysis method based on the weekly solution coordinate series of the station. With respect to the velocity of the IGS tracking station, it was better to model the variation periodically or to give a velocity periodically using a piece-wise linear function rather than a linear variable to estimate its bias.