This paper proposes a methodology for automatic, accurate, and early detection of amplitude ionospheric scintillation events, based on machine learning algorithms, applied on big sets of 50 Hz postcorrelation data provided by a global navigation satellite system receiver. Experimental results on real data show that this approach can considerably improve traditional methods, reaching a detection accuracy of 98%, very close to human-driven manual classification. Moreover, the detection responsiveness is enhanced, enabling early scintillation alerts.


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    Titel :

    Detection of GNSS Ionospheric Scintillations Based on Machine Learning Decision Tree


    Beteiligte:
    Linty, Nicola (Autor:in) / Farasin, Alessandro (Autor:in) / Favenza, Alfredo (Autor:in) / Dovis, Fabio (Autor:in)


    Erscheinungsdatum :

    01.02.2019


    Format / Umfang :

    3980424 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch