Improvement of RTK-GNSS with Low-Cost Sensors Based on Accurate Vehicle Motion Estimation Using GNSS Doppler

被引:0
作者
Takanose, Aoki [1 ]
Takikawa, Kanamu [1 ]
Arakawa, Takuya [1 ]
Meguro, Junichi [2 ]
机构
[1] Meijo Univ, Grad Sch Sci & Technol, Div Mechatron Engn, Tenpaku Ku, Shiogamaguti 1-501, Nagoya, Aichi, Japan
[2] Meijo Univ, Fac Sci & Technol, Dept Mechatron Engn, Nagoya, Aichi, Japan
来源
2020 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV) | 2020年
关键词
D O I
10.1109/iv47402.2020.9304539
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This study proposes a method for estimating the positions of vehicles in urban environments with high accuracy. We employ satellite positioning by GNSS for position estimation. Real-time kinematic-global navigation satellite systems (RTK-GNSS) with high precision in satellite positioning can estimate positions with centimeter-scale accuracy. However, in urban areas, the position estimation performance deteriorates owing to multipath errors. Therefore, we propose a method to improve the positioning results by increasing the robustness against multipath using vehicle trajectory. The vehicle trajectory estimates the travel route using the attitude angle and speed. Attitude angles are heading, pitching and slip angle. Trajectories can be generated with 0.5m error performance per 100m. In the proposed method, the trajectory is used as a constraint to solve the multipath of RTK-GNSS. In the evaluation test, the ratio of high-accuracy position estimation improved by up to approximately 30% compared to the conventional method. It is assumed that this method can enhance the development of self-driving cars, AGV control and SLAM technology by eliminating errors and calculating reliability.
引用
收藏
页码:658 / 665
页数:8
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