3次元点群の形状特長を利用したRTK-GNSS測位のMISSFIX検出

抄録

In the field of RTK-GNSS positioning technology, the occurrence of MISSFIX, a failure in determining confidence, poses a significant challenge. In this report, we present a novel approach to detecting MISSFIX by analyzing the shape features of the surrounding environment using GPS position information and 3D point clouds obtained from Lidar measurements. The proposed method utilizes persistent homology to extract features of the 3D environment reconstructed from 3D-Lidar point clouds. To identify situations in which GNSS position measurement errors occur, we introduce a method for determining GNSS measurement errors by comparing the features of the 3D point cloud recovered via odometry with those recovered from GNSS positions. This method has been demonstrated to be effective.