These days, many researchers are trying to apply Network RTK for land vehicle environment since the demand of high positioning accuracy for land vehicles is growing for many reasons especially for safety and user convenience. Network RTK requires smaller number of reference stations for covering the same area as well as maintains similar positioning accuracy compared to the conventional RTK. Therefore, it is highlighted to be appropriate for land vehicle applications. Unlike static users, kinematic users such as land vehicle users may experience network changes when they drive across the reference station networks. In Compact Network RTK, since carrier phase corrections of reference stations constituting each network are generated on different ambiguity levels, serious discontinuities can occur in corrections received by user, resulting from the changes of networks where the users belong. These discontinuities cause re-initialization for user integer ambiguity resolution, which takes several tens of seconds and user cannot get their precise position during the time of re-initialization. Therefore, we need to level integer ambiguities among networks in order that users can get consistent positioning accuracy. In this paper, we first formulate condition equations for ambiguity level and suggest a network leveling strategy based on double difference ambiguities and undifference ambiguities at master stations only. We select some reference station networks and collect real GPS data to analyze discontinuities in corrections and validate discontinuity reduction by ambiguity leveling.
展开▼
