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Research ArticleOriginal Article
Open Access

Spatiotemporal Deep Learning Network for High-Latitude Ionospheric Phase Scintillation Forecasting

Yunxiang Liu, Zhe Yang, Y. Jade Morton, and Ruoyu Li
NAVIGATION: Journal of the Institute of Navigation December 2023, 70 (4) navi.615; DOI: https://doi.org/10.33012/navi.615
Yunxiang Liu
1Department of Aerospace Engineering Sciences, University of Colorado Boulder, Colorado, USA
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  • For correspondence: [email protected]
Zhe Yang
1Department of Aerospace Engineering Sciences, University of Colorado Boulder, Colorado, USA
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Y. Jade Morton,
1Department of Aerospace Engineering Sciences, University of Colorado Boulder, Colorado, USA
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Ruoyu Li
2Department of Computer Science and Engineering, University of Texas at Arlington, Texas, USA
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  • FIGURE 1
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    FIGURE 1

    Illustration of the machine-learning-based forecasting procedure

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    FIGURE 2

    Illustration of the target station (blue) and surrounding auxiliary stations (yellow)

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    FIGURE 3

    Block diagram of the STDL network

    The target and surrounding GNSS stations are represented by blue and yellow dots, respectively.

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    FIGURE 4

    Performance comparison of ROC curves

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    FIGURE 5

    Performance comparison of precision–detection rate curves

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    FIGURE 6

    Performance comparison of ROC curves between STDL with external features (STDL-w/Ext) and without external features (STDL-noExt)

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    FIGURE 7

    Performance comparison of precision–detection rate curves between STDL with external features (STDL-w/Ext) and without external features (STDL-noExt)

Tables

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    TABLE 1

    List of Features in Local GNSS Measurements From Wu & Liu (2021)

    FeatureDescription
    Scintillation labelWhether scintillation occurred (binary)
    Mean S4Average value of S4 indices over all satellites in view
    Mean σϕAverage value of σϕ indices over all satellites in view
    Mean SNRAverage value of the SNR over all satellites in view
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    TABLE 2

    List of External Features (Wu & Liu, 2021)

    Observation CategoryFeatureDescription
    Space-basedBx (GSE)Solar wind interplanetary magnetic field (IMF) x component in geocentric solar ecliptic (GSE) system (J. H. King & Papitashvili, 2005)
    By (GSE)Solar wind IMF y component in GSE system (J. H. King & Papitashvili, 2005)
    Bz (GSE)Solar wind IMF z component in GSE system (J. H. King & Papitashvili, 2005)
    By (GSM)Solar wind IMF y component in geocentric solar magnetospheric (GSM) system (J. H. King & Papitashvili, 2005)
    Bz (GSM)Solar wind IMF z component in GSM system (J. H. King & Papitashvili, 2005)
    Magnetic field magnitudeMagnitude of solar wind IMF (J. H. King & Papitashvili, 2005)
    Vx velocity (GSE)Solar wind flow velocity x component in GSE system (J. H. King & Papitashvili, 2005)
    Vy velocity (GSE)Solar wind flow velocity y component in GSE system (J. H. King & Papitashvili, 2005)
    Vz velocity (GSE)Solar wind flow velocity z component in GSE system (J. H. King & Papitashvili, 2005)
    Flow speedSolar wind flow speed (J. H. King & Papitashvili, 2005)
    Proton densityPlasma proton density (J. H. King & Papitashvili, 2005)
    TemperaturePlasma temperature (J. H. King & Papitashvili, 2005)
    Flow pressureSolar wind flow pressure (J. H. King & Papitashvili, 2005)
    Electric fieldElectric field (Papitashvili, n.d.)
    Plasma betaBeta value of a plasma (Burke, n.d.; J. H. King & Papitashvili, 2005)
    Alfven speedSpeed of Alfven wave (J. H. King & Papitashvili, 2005)
    Lyman alphaSolar irradiance measurements of the bright H I 121.5-nm emission (Machol et al., 2019)
    Ground-basedAE indexAurora-electrojet index (Mandea & Korte, 2010)
    AL indexAL index (Mandea & Korte, 2010)
    AU indexAU index (Mandea & Korte, 2010)
    SYM indexSymmetric index (Mandea & Korte, 2010)
    ASY indexAsymmetric index (Mandea & Korte, 2010)
    PC(N) indexPolar cap index (Mandea & Korte, 2010)
    CCPCross cap potential (Greenwald et al., 1995)
    Kp indexKp index (Mandea & Korte, 2010)
    Sunspot numberSunspot number (Mandea & Korte, 2010)
    Dst indexDisturbance storm time index (Mandea & Korte, 2010)
    Ap indexAp index (Mandea & Korte, 2010)
    F10.710.7-cm-wavelength solar flux (McGranaghan et al., 2018; Tapping, 2013)
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    TABLE 3

    List of Features From Surrounding GNSS Stations (Wu & Liu, 2021)

    FeatureDescription
    Mean ROTIAverage value of ROTI over all satellites in view
    Median ROTIMedian value of ROTI over all satellites in view
    Mean ROTAverage value of ROT over all satellites in view
    Median ROTMedian value of ROT over all satellites in view

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NAVIGATION: Journal of the Institute of Navigation: 70 (4)
NAVIGATION: Journal of the Institute of Navigation
Vol. 70, Issue 4
Winter 2023
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Spatiotemporal Deep Learning Network for High-Latitude Ionospheric Phase Scintillation Forecasting
Yunxiang Liu, Zhe Yang, Y. Jade Morton,, Ruoyu Li
NAVIGATION: Journal of the Institute of Navigation Dec 2023, 70 (4) navi.615; DOI: 10.33012/navi.615

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Spatiotemporal Deep Learning Network for High-Latitude Ionospheric Phase Scintillation Forecasting
Yunxiang Liu, Zhe Yang, Y. Jade Morton,, Ruoyu Li
NAVIGATION: Journal of the Institute of Navigation Dec 2023, 70 (4) navi.615; DOI: 10.33012/navi.615
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    • 1 INTRODUCTION
    • 2 METHODOLOGY
    • 3 DATA SET DESCRIPTION
    • 4 PERFORMANCE EVALUATION
    • 5 CONCLUSIONS AND FUTURE WORK
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Keywords

  • forecast
  • ionospheric phase scintillation
  • machine learning

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