MISSFIX detection of RTK-GNSS positioning using 3D point clouds

-Methods using overlap of point clouds and shape features with persistent homology-

Abstract

RTK-GNSS positioning enables centimeter-level accuracy. Incorrect FIX determinations may exist in the positioning results, making it impossible to obtain accurate location. In this study, we propose two methods for detecting wrong FIX using point clouds obtained from 3D Lidar, posture data from IMU, and RTK-GNSS positioning data. One is extracting shape features based on persistent homology from the point clouds and comparing them. Another is comparing the overlap ratio of point cloud data measured at each positioning location. To demonstrate the effectiveness of the proposed methods, they were compared with the results of the Ratio Test.