In the process of application, unmanned aerial vehicles (UAVs) are faced with the threat of a complex electromagnetic environment, causing the airborne navigation system to fail to achieve ideal working conditions, and seriously restricting the overall effectiveness of the UAV system. Therefore, accurate assessment of UAV navigation system performance is an important prerequisite for scientific decision-making on the use of UAVs in complex environments in the future. In system design and experimentation, the more realistic electromagnetic interference environments that UAVs may be exposed to are difficult to build, resulting in insufficient data being collected to verify UAV navigation system performance. However, as real data from UAVs is continuously accumulated in various application scenarios at a later stage, it is necessary to explore a data mining-based method for UAV navigation system performance evaluation. In this study, a decision tree algorithm was used to construct a UAV navigation performance level classification assessment model. UAV performance was analysed through UAV navigation capability and survivability indicators. Finally, simulation experiments were conducted to further develop the construction and testing of the decision tree model. The experimental results showed that the model accuracy is above 90%, validating the feasibility of the method.


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    Titel :

    A Method for Evaluating the Performance of Unmanned Aerial Navigation Systems Based on Fuzzy Decision Trees


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Yang, Changfeng (Herausgeber:in) / Xie, Jun (Herausgeber:in) / Chen, Changyuan (Autor:in) / Shi, Chunlin (Autor:in) / Liu, Teng (Autor:in) / Li, Haojie (Autor:in) / Li, Qiyang (Autor:in) / Ma, Li (Autor:in)

    Kongress:

    China Satellite Navigation Conference ; 2022 ; Beijing, China May 22, 2022 - May 25, 2022



    Erscheinungsdatum :

    2022-05-07


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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