Classification of Ionospheric Scintillations during high Solar Activity and Geomagnetic Storm over Visakhapatnam Region using Machine Learning Approach

Abstract

The ionospheric plasma disturbances typically correlate with irregularities in electron density and ionospheric scintillations are produced in reaction to these variations generating radio signal fluctuations. Geolocation services and space based communication are endangered due to ionospheric scintillation which promptly produces fluctuations in information collected by Global Navigation Satellite Systems and this is at its strongest when the solar cycle is at its peak. Ionospheric space weather has a significant impact on Global Navigation Satellite Systems (GNSS) and one crucial aspect used in investigating ionospheric characteristics is total electron content (TEC). Due to fluctuations in time and space, the TEC obtained from GNSS signals is nonlinear and nonstationary. In this study, machine learning approaches for Classification of the ionospheric scintillations were used during the high solar activity and geomagnetic storm in the month of July 2023. This approach enables the classification of ionospheric phase scintillations using well-known classifiers: Decision Tree and Support Vector Machine.