Kriging Weighting Model of Network RTK for Ground Vehicle on Rainy Day

A network Real Time Kinematics (RTK) is applied for real time precise positioning of autonomous ground vehicles. However, there is a limit to achieve cm level accuracy due to degradation of the positioning performance of network RTK. The reason is that conventional weighting models of network RTK cannot reflect actual weather condition. In this paper, a Kriging weighting model and a variogram of rainy weather condition was used for cm level positioning of autonomous ground vehicle in rainy weather. As a result of simulation analysis for static and dynamic users, the conventional weighting model could not achieve cm level positioning accuracy in rainy weather, whereas using the Kriging weighting model with the suitable variogram could reliably achieve cm level positioning accuracy in rainy weather.