Research Article
A Novel Vehicular Integrated Positioning Algorithm
@INPROCEEDINGS{10.1007/978-3-319-44350-8_13, author={Jianqi Liu and Yanlin Zhang and Bi Zeng}, title={A Novel Vehicular Integrated Positioning Algorithm}, proceedings={Industrial IoT Technologies and Applications. International Conference, Industrial IoT 2016, GuangZhou, China, March 25-26, 2016, Revised Selected Papers}, proceedings_a={INDUSTRIALIOT}, year={2016}, month={9}, keywords={Vehicle positioning Information fusion Federate Kalman Filter Integrated positioning system}, doi={10.1007/978-3-319-44350-8_13} }- Jianqi Liu
Yanlin Zhang
Bi Zeng
Year: 2016
A Novel Vehicular Integrated Positioning Algorithm
INDUSTRIALIOT
Springer
DOI: 10.1007/978-3-319-44350-8_13
Abstract
The Global navigation satellite system (GNSS) can offer high precise location service for vehicle in open area, but in urban, the satellite signal is obscured by dense building, tunnel. Dead reckoning (DR) system can estimate vehicular position in short period of time, but do not work well as its error accumulation with the passage of time. If the area has been deployed RSU, vehicle can get own position by communication. A single positioning system is not able to offer precise location service in urban, this paper combines with RSU, GNSS and DR and proposes a integrated position system. The integrated system makes use of Federate Kalman Filter (FKF) algorithm to realize information fusion of three systems. The experimental results show the positioning accuracy and anti-jamming capability of RSU/GNSS/DR integrated positioning system is better than a single system.
