DocumentCode
787954
Title
A Low-Order DGPS-Based Vehicle Positioning System Under Urban Environment
Author
Huang, Jihua ; Tan, Han-Shue
Author_Institution
Gen. Motors Res. & Dev. Center
Volume
11
Issue
5
fYear
2006
Firstpage
567
Lastpage
575
Abstract
The vehicle positioning system is a key component in functions such as vehicle guidance, driver alert and assistance, and vehicle automation. Since installing a low-cost global positioning system (GPS) or inertial navigation system (INS) unit is becoming a common practice in vehicle applications, its involvement in vehicle guidance and vehicle safety deserves a closer investigation. Typical vehicle applications require high reliability, low cost, and sufficient accuracy under all operational conditions. For GPS-based positioning, urban driving with its complicated maneuvers, frequent GPS blockage, and multipath, are some of the most difficult driving environments. This paper explores the feasibility of a low-order vehicle positioning system functioning under an urban environment. The equipped vehicle has a midrange differential GPS (DGPS) unit and few relatively simple in-vehicle sensors. A low-order integration is explored by utilizing a vehicle model-based extended Kalman filter (EKF) to incorporate in-vehicle motion sensors and to largely avoid direct integration of INS signals. Further, the characteristics of DGPS measurements under urban environments are investigated, and novel DGPS noise processing techniques are proposed to reduce the chances of exposing the EKF to undesirable DGPS measurements due to common DGPS problems such as blockage and multipath. A resulting fourth order EKF based positioning system is successfully implemented in the test vehicle to demonstrate the feasibility of the proposed design. Experimental results illustrate the ability of the system to meet the accuracy and robustness requirements in the presence of blockage and multipath under a typical urban driving environment
Keywords
Global Positioning System; Kalman filters; control engineering computing; inertial navigation; nonlinear filters; position control; road vehicles; traffic information systems; DGPS; differential global positioning system; driver alert; driver assistance; extended Kalman filter; inertial navigation system; urban driving; vehicle automation; vehicle guidance; vehicle positioning system; Automation; Costs; Global Positioning System; Inertial navigation; Noise measurement; Noise reduction; Sensor phenomena and characterization; Vehicle driving; Vehicle safety; Working environment noise; DGPS/inertial navigation system (INS) integration; differential GPS (DGPS); extended Kalman filter (EKF); global positioning system (GPS); urban environment; vehicle positioning;
fLanguage
English
Journal_Title
Mechatronics, IEEE/ASME Transactions on
Publisher
ieee
ISSN
1083-4435
Type
jour
DOI
10.1109/TMECH.2006.882988
Filename
1709862
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