Improvement of GPS and BeiDou extended orbit predictions with CNNs

Jaakko Pihlajasalo, Helena Leppäkoski, Simo Ali-Löytty, Robert Piché

    Tutkimustuotos: KonferenssiartikkeliScientificvertaisarvioitu

    3 Sitaatiot (Scopus)
    203 Lataukset (Pure)

    Abstrakti

    This paper presents a method for improving the accuracy of extended GNSS satellite orbit predictions with convolutional neural networks (CNN). Satellite orbit predictions are used in self-assisted GNSS to reduce the Time to First Fix of a satellite positioning device. We describe the models we use to predict the satellite orbit and present the improvement method that uses CNN. The CNN estimates future prediction errors of our model and these estimates are used to correct our orbit predictions. We also describe how the neural network can be implemented into our prediction algorithm. In tests with GPS and BeiDou data, the method significantly improves orbit prediction accuracy. For example, the 68% error quantile of 7 day orbit prediction errors of GPS satellites was reduced by 45% on average.

    AlkuperäiskieliEnglanti
    Otsikko26th European Navigation Conference, ENC 2018
    AlaotsikkoGothenburg, Sweden, 14-17 May, 2018
    KustantajaIEEE
    Sivut54-59
    Sivumäärä6
    ISBN (painettu)9781538649626
    DOI - pysyväislinkit
    TilaJulkaistu - 10 elok. 2018
    OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
    TapahtumaEuropean Navigation Conference -
    Kesto: 20 syysk. 2018 → …

    Conference

    ConferenceEuropean Navigation Conference
    Ajanjakso20/09/18 → …

    Julkaisufoorumi-taso

    • Jufo-taso 1

    !!ASJC Scopus subject areas

    • Computer Networks and Communications
    • Signal Processing
    • Control and Optimization

    Sormenjälki

    Sukella tutkimusaiheisiin 'Improvement of GPS and BeiDou extended orbit predictions with CNNs'. Ne muodostavat yhdessä ainutlaatuisen sormenjäljen.

    Siteeraa tätä