Real-time high-precision landslide displacement monitoring based on a GNSS CORS network

Abstract

GNSS technology is an effective all-weather, continuous and real-time method of detecting three-dimensional landslide displacement. However, current positioning methods such as the network real-time kinematic (RTK) technique based on virtual reference station (VRS) technology have some limitations, particularly a sensitivity to atmospheric modeling error. In this study, taking advantage of existing GNSS continuously operating reference stations (CORS), we propose a network RTK algorithm (virtual atmosphere constraint (VAC)) for high-precision landslide monitoring. Network modeling atmosphere delays were used as virtual observations for the terminal position solution, by which their accuracy information can be considered. Additionally, a noise reduction method that combines complementary ensemble empirical mode decomposition and median filtering was proposed to reduce GNSS signal residual errors in the original RTK coordinate time series. To validate the effectiveness of the algorithm, we processed one week of data from two monitoring receivers on the Heifangtai landslide and four surrounding CORS using the VAC and VRS methods. Results show that the original displacement time series processed with VRS was prone to jitter, whereas the VAC method exhibited better accuracy, stability, and ambiguity fixing rates. Horizontal and vertical RMS errors at a stable monitoring point were 1.7 cm and 3.9 cm for VRS-RTK and 0.9 cm and 2.3 cm for VAC-RTK; thus, VAC reduced the error by 40.1% and 20.5%, respectively. After noise reduction, the RMS values of the VAC method at the stable and the other collapsed monitoring point were both reduced to an mm-level accuracy.