Title :
Multi-sensor fusion vehicle positioning based on Kalman Filter
Author :
Guan, Hsin ; Li, Luhao ; Jia, Xin
Author_Institution :
State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, China
Abstract :
With the development of the intelligent vehicle navigation systems and vehicle networking systems, vehicle positioning and state estimation become very important. This paper investigates the integration of Global Positioning System (GPS), Inertial Navigation System (INS) and Dead Reckoning based on Anti-lock Braking System (ABSDR) positioning based on Kalman filter, and aims at achieving full-time vehicle positioning. In this paper, we use Kalman Filter to estimate INS positioning error based on GPS or ABSDR solution, take the INS solution compensated with estimated error as system output. This paper introduces INS positioning algorithm, dead reckoning method based on the ABS wheel speed and Kalman filtering method. After that, simulation analysis and experimental verification of the positioning algorithm are carried out. The results show that the system output high-precision high-frequency positioning information when GPS is available, and when GPS is unavailable, INS positioning errors can be compensated well with ABSDR introduced, achieving the full-time positioning of the vehicle.
Keywords :
Educational institutions; Equations; Global Positioning System; Kalman filters; Mathematical model; Vehicles; Wheels;
Conference_Titel :
Information Science and Technology (ICIST), 2013 International Conference on
Conference_Location :
Yangzhou
Print_ISBN :
978-1-4673-5137-9
DOI :
10.1109/ICIST.2013.6747554