This paper proposes a multi-sensor positioning technology for unmanned aerial vehicle (UAV) landing based on inertial navigation system (INS)/Global navigation satellite system (GNSS)/Radar integrated guidance system. In the harsh environment where sensor prior information is unreliable, measurement noise is non-stationary and measurement outliers are frequently generated, an adaptive federated filter based on variational Bayesian is used to achieve high accuracy and robustness of navigation system. Simulation results demonstrate that this guidance technology has a strong ability to adapt to non-stationary noise and frequent outliers, and the fusion accuracy is satisfactory.


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    Titel :

    Multi-sensor Data Fusion for UAV Landing Based on Federal Variational Bayesian Filtering


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Fu, Wenxing (Herausgeber:in) / Gu, Mancang (Herausgeber:in) / Niu, Yifeng (Herausgeber:in) / Li, Yifan (Autor:in) / Hu, Jinwen (Autor:in) / Zhao, Chunhui (Autor:in) / Xu, Zhao (Autor:in) / Lv, Mingwei (Autor:in) / Wang, Wenzhe (Autor:in)

    Kongress:

    International Conference on Autonomous Unmanned Systems ; 2022 ; Xi'an, China September 23, 2022 - September 25, 2022



    Erscheinungsdatum :

    10.03.2023


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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