中國(guó)有色金屬學(xué)報(bào)(英文版)
Transactions of Nonferrous Metals Society of China
| Vol. 24 No. 2 February 2014 |
（1. School of Environment and Spatial Information,
China University of Mining and Technology, Xuzhou 221116, China;
2. Key Laboratory of Land Environment and Disaster Monitoring of SBSM,
China University of Mining and Technology, Xuzhou 221116, China）
Abstract: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.
Key words: mining subsidence; global navigation satellite system (GNSS); Robust Kalman Filtering (RKF); IGS station
