In this paper, a multi-sensor fusion based environment perception architecture for ground unmanned vehicles is proposed. The target-level multi-sensor fusion technology is presented to take advantages of camera and millimeter wave (MMW) radar in target perception. On this basis, a multi-target tracking model is designed to solve the problems of alignment, association, uncertainty, as well as the elimination of false data. In order to verify the stability and real-time performance of the proposed algorithm, a real vehicle test was implemented according to the statistical data and relevant indicators. The results show that the proposed algorithm can effectively perceive and track multiple obstacles in real scene.


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    Titel :

    Radar and Camera Fusion based Moving Obstacle Tracking for Automated Vehicles


    Beteiligte:
    Wang, Shihao (Autor:in) / Ma, Zheng (Autor:in) / Li, Ying (Autor:in) / Yang, Chao (Autor:in) / Wang, Weida (Autor:in) / Xiang, Changle (Autor:in)


    Erscheinungsdatum :

    29.10.2021


    Format / Umfang :

    2865587 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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