1. Real-time Solar Flare detector using GNSS signals: results, characterization and performance improvement
- Author
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Universitat Politècnica de Catalunya. Departament de Matemàtiques, Aragón Ángel, María Ángeles, Timoté Bejarano, Cristhian Camilo, Guitart Palonsky, Gonzalo, Universitat Politècnica de Catalunya. Departament de Matemàtiques, Aragón Ángel, María Ángeles, Timoté Bejarano, Cristhian Camilo, and Guitart Palonsky, Gonzalo
- Abstract
The effects of the Sun on the Earth’s upper atmosphere, known as the ionosphere, and their implications for satellite-ground communication and ground infrastructures are of significant importance not only for the aerospace industry but also for the communications field. In this thesis, a study on Solar Flares (SF) has been conducted, which are sudden emissions of electromagnetic radiation from the Sun lasting from minutes to hours. To investigate this phenomenon, a technique based on Global Navigation Satellite System (GNSS) has been employed, detecting one of the Solar Flares effects (SFe), which is specifically the enhancement of Total Electron Content (TEC) in the ionosphere, resulting in delays in GNSS signals. By understanding the typical behavior of the ionosphere, sudden variations in TEC can be discriminated, allowing for the establishment of thresholds to determine when a Solar Flare has occurred. The GNSS Solar Flare detector (GNSS-SF) had been previously tested over an 11 year period. However, in the year 2023, coinciding with a solar maximum, the objective of this thesis is to demonstrate that increasing the sampling rate from 30 seconds to 5 seconds improves the performance of the GNSS-SF. This was achieved through a statistical analysis spanning almost 330 days between the two implementations, comparing GNSS-SF detections with those provided by the Geostationary Operational Environmental Satellites (GOES). It has been concluded that the implementation at a 5-second rate yields superior results and detects Solar Flares that the 30 second implementation fails to detect.
- Published
- 2024