Adaptive Fast Independent Component Analysis Methods for Mitigating Multipath Effects in GNSS Deformation Monitoring

Abstract

Carrier-phase multipath is the main problem of GNSS deformation monitoring. Traditional methods usually adopt sidereal day filtering to mitigate the multipath. However, the necessity of presetting the session duration of the static baseline solution reduces the timeliness of the methods in real engineering. Moreover, these methods are not suitable for the systems that contain different types of GNSS satellites (e.g., BDS). To address the problems, this paper proposes an Adaptive Fast Independent Component Analysis (AF-ICA) method for mitigating multipath effects in GNSS deformation monitoring, which can effectively process the multi-GNSS data and separate several multipath signals. In the experimental study, compared with Sidereal Filtering in Observation Domain (SF-OD) method, AF-ICA method can improve both the positioning accuracy and peak-to-peak value. In GNSS deformation monitoring positioning accuracy, AF-ICA method can achieve the root-mean-square (RMS) of 1 mm horizon-tally and 2 mm vertically. Compared with the MSF method, the positioning accuracy of the AF-ICA method in the direction of ENU is improved by 44%, 14%, and 31%, respectively, and the corresponding peak-to-peak values increased by 36%, 17%, and 29%, respectively. Our proposed method can automatically get the monitoring information without estimating the orbit period in advance to realize automatic deformation monitoring. Through the automatic monitoring solution, the AF-ICA method in this paper can be applied to the natural disaster monitoring in the Internet of Things and provides real-time data monitoring information for disaster early warning.