Research On Vehicle Positioning Technology In Blind Area Of Vehicle Networking

In current Internet of Vehicles, how to get the precise vehicle positions in blind area is not only a hot research focus but also a major challenge. GNSS(Global Navigation Satellite System) is capable of positioning accurately and globally, but sometimes the signal may be sheltered so that GNSS is unavailable in blind area. INS(Inertial Navigation System) is independent and anti-interference, but the positioning error will accumulate, which causes INS useless in blind area for a long time. This thesis analyses a current simple and practical vehicle autonomous positioning technique that is applied in blind area, then uses the map matching algorithms and modified algorithms to solve the problem of error accumulation. The main work are listed as follows:1.This thesis analyses a current simple and practical vehicle autonomous positioning technique named VSYR(Vehicle Speed and Yaw Rate), then establishes simple and complex mathematical models respectively for research. The theoretical analyses and simulation results show that VSYR has the problem of error accumulation like INS, which is due to the inaccurate parameters of vehicle sensors;2.This thesis studies a map matching technique to correct the parameters of vehicle sensors. It uses VSYR to get the vehicle positions and corrects the vehicle positions with map matching algorithms, which could correct the parameters of vehicle sensors. The simulation results show that this technique could reduce the accumulated error effectively;3.This thesis studies a technique to correct the parameters of vehicle sensors when GNSS is visible. When GNSS is visible, this technique uses VSYR and GNSS respectively to get the vehicle positions, then corrects the GNSS positioning points through map matching algorithms, which coule correct the parameters of vehicle sensors. The simulation results show that this technique could reduce the accumulated error effectively.