TEC modelling via neural network using observations from the first GLONASS R&D data network in Brazil and the RBMC

Abstract

This work presents a result on the use of neural networks (NNs) model to estimate Total Electron Content (TEC) behavior based on Global Navigation Satellite Systems (GNSS) measurements in the Brazilian equatorial and low latitude sectors. The main goal of the proposed NN is to estimate GPS (Global Positioning System) TEC values at locations without a GNSS receiver that may be used, for instance, as background models in regional TEC mapping procedures. The proposed approach is useful especially for single frequency users that rely on corrections of ionospheric range errors by TEC models. The data used was collected on the first GLONASS (Globalnaya Navigatsionnaya Sputnikovaya Sistema) network for research and development (GLONASS R&D network), recently inaugurated in Brazil, and also on the Brazilian Network for Continuous Monitoring of the GNSS Systems (RBMC), with a temporal interval of 15s or 30s and a spatial resolution of about 300 km over an area corresponding to a longitudinal extension of 650 km. The input parameters for the NN used in this work are the latitude, longitude, day of the year (doy), time of the day, the global geomagnetic storm index (Kp-index), and the solar radio flux at 10.7 cm, and the output the vertical TEC (vTECe). The vTEC used for training the NN is calculated with the GPS-TEC Analysis Application, version 2.9.3. Future work considers applying the vTEC calculated with the ICTP method in the training process which allows the use of both GPS and GLONASS TEC. Information on the new GLONASS R&D network, future research possibilities and collaborations are also provided.