This paper describes the theoretical development and evaluation of the multisensor navigation system for high speed road vehicle. The paper focuses on the design of the nonlinear process model that is able to cope with vehicle slip using multisensor data from the inertial sensors, odometry, and D-GPS. The algorithm was evaluated using a vehicle dynamics simulator built to allow the simulation of a wide variety of driving scenarios. The simulation results show that the scheme is able to significantly reduce the errors in vehicle position and orientation estimates. They also show that the scheme allows slip angle estimation and accelerometer bias estimation.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    High accuracy road vehicle state estimation using extended Kalman filter


    Beteiligte:
    Wada, M. (Autor:in) / Kang Sup Yoon, (Autor:in) / Hashimoto, H. (Autor:in)


    Erscheinungsdatum :

    01.01.2000


    Format / Umfang :

    447848 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    High Accuracy Road Vehicle State Estimation Using Extended Kalman Filter

    Wada, M. / Yoon, K. S. / Hashimoto, H. et al. | British Library Conference Proceedings | 2000


    Vehicle Dynamics and Road Slope Estimation based on Cascade Extended Kalman Filter

    Kim, Moon-sik / Kim, Beom-jae / Kim, Chang-il et al. | IEEE | 2018



    Dual extended Kalman filter for vehicle state and parameter estimation

    Wenzel,T.A. / Burnham,K.J. / Blundell,M.V. et al. | Kraftfahrwesen | 2006


    Dual extended Kalman filter for vehicle state and parameter estimation

    Wenzel, T. A. / Burnham, K. J. / Blundell, M. V. et al. | Taylor & Francis Verlag | 2006