DocumentCode :
2121401
Title :
Hybridized GPS/DR Positioning System With Unknown Initial Heading For Land Vehicles
Author :
Dumitrache, A. ; Zamora, M.A. ; Toledo-Moreo, R. ; Skarmeta, A.G.
Author_Institution :
Centre for Res. & Training in Ind. Control, Tech. Univ. of Bucharest, Bucharest
fYear :
2008
fDate :
12-15 Oct. 2008
Firstpage :
974
Lastpage :
979
Abstract :
In the intelligent transportation systems (ITS) field, the number of applications that demand a high integrity positioning system is growing. In order to improve the integrity of localization systems, GPS is usually hybridized with additional proprioceptive sensors. In this paper, a new hybridization algorithm based on GPS plus odometry and a gyro is proposed as an improvement of the most common extended Kalman filter (EKF) approach. In concrete, these investigations focus on the performance of the system under bad initial conditions. Results show the suitability of the proposed system for navigation under bad initial values of heading, and its benefits as compared to two state-of-the-art methods of the literature: an EKF, and a particle filter based solution.
Keywords :
Global Positioning System; Kalman filters; automated highways; distance measurement; nonlinear filters; particle filtering (numerical methods); road vehicles; sensor fusion; EKF; ITS; data fusion; extended Kalman filter; gyro; hybridized GPS/DR positioning system; intelligent transportation system; land vehicle; localization system; odometry; particle filter; proprioceptive sensor; unknown initial heading; Costs; Global Positioning System; Intelligent sensors; Intelligent transportation systems; Land vehicles; Navigation; Particle filters; Road vehicles; Sensor fusion; Sensor systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Transportation Systems, 2008. ITSC 2008. 11th International IEEE Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2111-4
Electronic_ISBN :
978-1-4244-2112-1
Type :
conf
DOI :
10.1109/ITSC.2008.4732633
Filename :
4732633
Link To Document :
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