IMPROVEMENT OF CHANGE POINT DETECTION METHOD OF RTK-GNSS DATAIN IN SLOPE MANAGEMENT

Abstract

In recent years, unpredictable slope failures caused by extreme weather have been increasing in Japan. Management companies are required to detect the slope failure quickly to ensure the safety of expressway users. In order to solve this problem, a new change point detection system is proposed to detect unpredictable slope deformation by using Change Finder with SDAR algorithm for RTK-GNSS data. However, there are still problems with detection accuracy. In this research, we attempted to improve the detection accuracy of Change Finder by preprocessing multipath errors and random errors included in the data of satellite positioning system, RTK-GNSS. Specifically, sidereal time-based differential method was applied to the processing of multipath errors, Low path filter was applied to the processing of random errors. As a result, the detection probability by Change Finder was significantly improved.