• 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