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.


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    Titel :

    A Vehicle Tracking Algorithm Based on Extended Kalman Filtering


    Beteiligte:
    Lu, Shengnan (Autor:in) / Yan, Ting (Autor:in)


    Erscheinungsdatum :

    21.04.2023


    Format / Umfang :

    1915768 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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