Artificial intelligence used in unmanned aerial vehicle (UAV) flight control systems tends to leave UAV control systems without any radio communication emissions, whose signatures in an electromagnetic spectrum (ES) are widely used to detect UAVs. There will be problems in the near future in detecting any dangerous threats associated with UAV swarms, kamikaze unmanned aerial vehicles (UAVs), or any other UAVs with electrically powered thrust engines because of the UAV’s flight capabilities in full radio silence mode. This article presents a different approach to the detection of electrically powered multi-rotor UAVs. The main idea is to register the electromagnetic spectrum of the electric thrust engines of the UAV, which varies because of the changing flight conditions. An experiment on a UAV’s electric thrust engine-produced electromagnetic spectrum is carried out, presenting the results of the flight-dependent characteristics, which were observed in the electromagnetic spectrum. The electromagnetic signature of the UAV’s electric thrust engines is analyzed, discussed, and compared with the most similar behaving electric engine, which was used on the ground as a domestic electric appliance. A precision tunable magnetic antenna is designed, manufactured, and tested in this article. The physical experiments have shown that the ES of the electric thrust engines of multi-rotor UAVs can be detected and recorded for recognition. The unique signatures of the ES of the multi rotor UAV electric engine are recorded and presented as a result of the carried-out experiments. A precision tunable magnetic antenna is evaluated for the reception of the UAV’s signature. Moreover, results were obtained during the performed experiments and discussions about the development of the future techniques for the identification of the ES fingerprints of the UAV’s electric thrust engine are carried out.


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    Titel :

    UAV Detection Using Thrust Engine Electromagnetic Spectra


    Beteiligte:


    Erscheinungsdatum :

    2022




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




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