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Title:

Ionospheric VTEC Forecasting using Machine Learning

Document type:
Konferenzbeitrag
Contribution type:
Vortrag / Präsentation
Author(s):
Natras R., Schmidt M.
Abstract:
The accuracy and reliability of Global Navigation Satellite System (GNSS) applications are affected by the state of the Earth‘s ionosphere, especially when using single frequency observations, which are employed mostly in mass-market GNSS receivers. In addition, space weather can be the cause of strong sudden disturbances in the ionosphere, representing a major risk for GNSS performance and reliability. Accurate corrections of ionospheric effects and early warning information in the presence of...     »
Keywords:
Machine Learning, Ionosphere, VTEC, Space Weather
Book / Congress title:
European Geosciences Union (EGU) General Assembly
Date of congress:
2021-04-19/30
Year:
2021
Year / month:
2021-04
Fulltext / DOI:
doi:10.5194/egusphere-egu21-8907
TUM Institution:
Deutsches Geodätisches Forschungsinstitut (DGFI-TUM)
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