UAV navigation and positioning research is critical to flight safety, complex environment response and aviation technology advancement. Global research has focused on multi-sensor fusion and visual navigation, but challenges such as positioning accuracy, multi-modal fusion and real-time performance still need to be addressed. Continued in-depth research will improve UAV positioning accuracy, environment awareness and autonomous navigation capabilities, and promote the expansion of UAV technology applications. This paper focuses on the advantages of radar and unmanned aerial vehicles (UAVs), such as strong concealment and anti-jamming, which are one of the key equipments in modern military operations. The existing passive positioning methods have the defect of large target positioning error, which cannot meet the needs of today's warfare. Therefore, this study proposes a UAV positioning and formation analysis based on passive dual-station positioning and optimised models. The results show that the model proposed in this study has good robustness.


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    Titel :

    UAV localisation and formation analysis based on passive dual-station localisation and after optimised models


    Beteiligte:
    Tosti, Fabio (Herausgeber:in) / Bilal, Muhammad (Herausgeber:in) / Li, Hengyuan (Autor:in) / Guo, Yingshan (Autor:in) / Bai, Yunxiao (Autor:in) / Liu, Enbo (Autor:in)

    Kongress:

    Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023) ; 2023 ; Qingdao, China


    Erschienen in:

    Proc. SPIE ; 12797 ; 127972Z


    Erscheinungsdatum :

    30.08.2023





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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