Accurate ship tracking is one of the important means to implement accurate ship monitoring and reduce traffic accidents. The traditional ship tracking is based on the single sensor source such as VTS, AIS or CCTV to realize the data processing. The accuracy of single data source is not high, and it is difficult to meet the requirements of water transportation management. In order to improve the accuracy of ship tracking, a distributed ship tracking algorithm based on particle filter is proposed, and it integrates AIS and CCTV data. At the edge of CCTV, YOLO technology is used to identify ships and the identified status information is returned to the cloud. by the distributed parallel particle filter, the cloud realizes the prediction of ship state from AIS data, and the correction of ship state from CCTV data. The experimental results show that the proposed algorithm can track the ship state more effective and accurate than the traditional ship tracking algorithm.


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    Titel :

    A distributed ship tracking algorithm based on particle filter


    Beteiligte:
    Lv, Taizhi (Autor:in) / Yu, Miao (Autor:in) / Han, Yu (Autor:in) / Chen, Yong (Autor:in)


    Erscheinungsdatum :

    01.02.2022


    Format / Umfang :

    2248042 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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