Method for forecasting ionospheric electron content fluctuations based on the optical flow algorithm

• Published in: IEEE Transactions on Geoscience and Remote Sensing
• Main Authors: Monte Moreno, Enrique, Hernández Pajares, Manuel, Yang, Heng, García Rigo, Alberto, Jin, Yaqi, Høeg, Per, Miloch, Wojciech J., Wielgosz, Pawel, Jarmolowski, Wojciech, Paziewski, Jacek, Milanowska, Beata, Hoque, Mainul, Orús Pérez, Raul
• Other Authors: Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions, Universitat Politècnica de Catalunya. Departament de Matemàtiques, Universitat Politècnica de Catalunya. VEU - Grup de Tractament de la Parla, Universitat Politècnica de Catalunya. IonSAT - Grup de determinació Ionosfèrica i navegació per SAtèl·lit i sistemes Terrestres
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2022
• Subjects: Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica; Global Positioning System; Radio waves > Scintillation; Forecast; Global navigation satellite system (GNSS); Optical flow method; Rate of change of total electron content index (ROTI); Scintillation; TEC fluctuations; Sistema de posicionament global; Greenland
• Online Access: http://hdl.handle.net/2117/365213; https://doi.org/10.1109/TGRS.2021.3126888

We present the optical flow algorithm for forecasting the rate of total electron content index (OFROTI). It consists of a method for predicting maps of rapid fluctuations of ionospheric electron content in terms of global navigation satellite system (GNSS) dual-frequency phase measurements of the rate of change of total electron content index (ROTI). The forecast is made in space and time, at horizons up to more than 6 h. These forecast maps will consist of the ROTI spatial distribution in the northern hemisphere above 45° latitude. The prediction method models the ROTI spatial distribution as a pseudoconservative flux, i.e., exploiting the inertia of the flux of ROTI to determine the future position. This idea is implemented as a modification of the optical flow image processing technique. The algorithm has been modified to deal with the nonconservation of the ROTI quantity in time. We show that the method can predict both, the local value of ROTI and also the regions with ROTI above a given level, better than the prediction using the current map as forecast, i.e., predicting by a current map from horizons of 15 min up to 6 h. The method was tested on 11 representative active and calm days during 2015 and 2018 from the multi-GNSS (GPS, GLONASS, Galileo, and Beidou) multifrequency measurements of more than 250 multi-GNSS receivers above 45°N latitude, including the high rate (1 Hz) measurements of Greenland geodetic network (GNET) network among the International GNSS Service network. This work is funded by ESA ITT “Forecasting Space Weather Impacts on Navigation Systems in the Arctic (Green-land Area)” Expro+, Activity No. 1000026374. The GNET GNSS observations from Greenland was kindly provided by The Danish Agency for Data Supply and Efficiency, in the Danish Ministry of Energy, Utilities and Climate, Copenhagen, Denmark Peer Reviewed Postprint (author's final draft)