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Found 4 entries in the Bibliography.
Showing entries from 1 through 4
| 2022 |
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Scintillation due to ionospheric plasma irregularities remains a challenging task for the space science community as it can severely threaten the dynamic systems relying on space-based navigation services. In the present paper, we probe the ionospheric current and plasma irregularity characteristics from a latitudinal arrangement of magnetometers and Global Navigation Satellite System (GNSS) stations from the equator to the far low latitude location over the Indian longitudes, during the severe space weather events of 6–10 ... Vankadara, Ram; Panda, Sampad; Amory-Mazaudier, Christine; Fleury, Rolland; Devanaboyina, Venkata; Pant, Tarun; Jamjareegulgarn, Punyawi; Haq, Mohd; Okoh, Daniel; Seemala, Gopi; Published by: Remote Sensing Published on: jan YEAR: 2022 DOI: 10.3390/rs14030652 space weather; equatorial plasma bubbles; ionospheric irregularity; global navigation satellite system; magnetometer; poleward drift; rate of change of TEC index; scintillations; storm-time electric currents |
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In high latitudes, Global Navigation Satellite System (GNSS) signals experience scintillation due to moving irregularity structures in the ionosphere. These develop as a result of different physical mechanisms, which are as yet principally described on an elementary level for certain storm cases and events. Since there are years of GNSS data available from stations around the globe, we are investigating an unsupervised Machine Learning approach to extract a large variety of groups of scintillation events with similar feature ... Bals, Anna-Marie; Thakrar, Chintan; Deshpande, Kshitija; Published by: IEEE Journal of Radio Frequency Identification Published on: YEAR: 2022 DOI: 10.1109/JRFID.2022.3163913 Databases; Feature extraction; Fluctuations; global navigation satellite system; GNSS data noise elimination; GNSS scintillation; Indexes; Instruments; ionospheric scintillation event detection; Radiofrequency identification; unsupervised machine learning |
| 2021 |
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Assessment of the predictive capabilities of NIGTEC model over Nigeria during geomagnetic storms The Nigerian Total Electron Content (NIGTEC) is a regional neural network-based model developed by the Nigerian Centre for Atmospheric Research to predict the Total Electron Content (TEC) at any location over Nigeria. The addition of the disturbance storm time (Dst) index as one of NIGTEC s input layer neurons raises a question of its accuracy during geomagnetic storms. In this paper, the capability of NIGTEC in predicting the variability of TEC during geomagnetic storms has been assessed. TEC data predicted by NIGTEC is com ... Amaechi, Paul; Humphrey, Ibifubara; Adewoyin, David; Published by: Geodesy and Geodynamics Published on: nov YEAR: 2021 DOI: 10.1016/j.geog.2021.09.003 geomagnetic storm; global navigation satellite system; Nigerian Total Electron Content (NIGTEC); total electron content |
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Effects of the 12 May 2021 Geomagnetic Storm on Georeferencing Precision In this work, we present the positioning error analysis of the 12 May 2021 moderate geomagnetic storm. The storm happened during spring in the northern hemisphere (fall in the south). We selected 868 GNSS stations around the globe to study the ionospheric and the apparent position variations. We compared the day of the storm with the three previous days. The analysis shows the global impact of the storm. In the quiet days, 93\% of the stations had 3D errors less than 10 cm, while during the storm, only 41\% kept this level o ... Valdés-Abreu, Juan; Díaz, Marcos; Báez, Juan; Stable-Sánchez, Yohadne; Published by: Remote Sensing Published on: jan YEAR: 2021 DOI: 10.3390/rs14010038 Geomagnetic storms; total electron content; global navigation satellite system; Global positioning system; precise point positioning; rate of change of the tec index |
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