Autonomous vehicles such as drones and self-driving cars have been used in recent years. Many autonomous vehicles use the global positioning system (GPS) to acquire location data, which requires high accuracy. On the other hand, electromagnetic (EM) environment inside the autonomous vehicle is complicated since EM noise sources and a GPS antenna are densely mounted. This environment may degrade the accuracy of positioning measurements by EM interference between EM noise and GPS signals. Previous studies have reported the interference of EM noise with global navigation satellite system (GNSS) and with the mobile communications used by drones. Evaluations and countermeasures for the EM interference problems are necessary since the accuracy degradation of positioning measurements may lead to contact accidents between aircraft. In this study, we evaluated the EM interference between EM noise and GPS signals. There are two setups for the evaluation, the actual setup using a GPS receiver module and the simulation setup. These two evaluation setups were confirmed to be quantitative and reliable by the EM interference evaluation using random noise. Finally, we evaluated the impact of EM interference by EM noise from a commercial drone, one of the autonomous vehicles, on the GPS receiving sensitivity. The sensitivity degraded by about 10 dB in the actual evaluation and by about 11 dB in the simulation evaluation. This result shows that the EM noise from autonomous vehicles has a huge impact on the sensitivity of GPS.


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    Titel :

    Evaluation of Electromagnetic Interference Between Electromagnetic Noise from an Autonomous Vehicle and GPS Signals


    Beteiligte:
    Uehara, Hiraku (Autor:in) / Watanabe, Koh (Autor:in) / Sakai, Ryota (Autor:in) / Ashida, Sosuke (Autor:in) / Tanaka, Satoshi (Autor:in) / Nagata, Makoto (Autor:in)


    Erscheinungsdatum :

    20.05.2024


    Format / Umfang :

    532033 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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