This paper is based on the actual application scenario of vehicles driving on the road. In order to better capture the apparent characteristics of vehicles, this paper proposes a target tracking algorithm based on improved Kalman filter in the tracking stage. The extended Kalman filter is used to track the vehicle. The state of the target is predicted and updated, and the predicted target is improved according to the linear model of the Kalman filter to further optimize the accuracy and precision of the vehicle target during the tracking process. The experimental results show that both accuracy and precise have been significantly improved, while identity switch has also decreased, thereby reducing the missed detection rate and false detection rate to a certain extent.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Vehicle Tracking Algorithm Based on Extended Kalman Filtering


    Contributors:
    Lu, Shengnan (author) / Yan, Ting (author)


    Publication date :

    2023-04-21


    Size :

    1915768 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Finite-Difference Extended Kalman Filtering Algorithm for Ballistic Target Tracking

    Wu, C. / Han, C. | British Library Online Contents | 2008


    Extended Kalman Filtering

    Musoff, Howard / Zarchan, Paul | AIAA | 2009


    Extended Kalman Filtering

    Musoff, Howard / Zarchan, Paul | AIAA | 2005


    Extended Kalman Filtering

    Zarchan, Paul / Musoff, Howard | AIAA | 2015


    Deterministic sampling-based switching kalman filtering for vehicle tracking

    Veeraraghavan, H. / Papanikolopoulos, N. / Schrater, P. | IEEE | 2006