Related papers: Ionospheric activity prediction using convolutiona…
The ionosphere critically influences Global Navigation Satellite Systems (GNSS), satellite communications, and Low Earth Orbit (LEO) operations, yet accurate prediction of its variability remains challenging due to nonlinear couplings…
Ionosphere has an important role in long distance HF communications, satellite communications and global navigation systems. Ionosphere is a plasma medium which arises due to solar and cosmic radiation, and the amount of ionization is…
The ionosphere is a vitally dynamic charged particle region in the Earth's upper atmosphere, playing a crucial role in applications such as radio communication and satellite navigation. The Slant Total Electron Contents (STEC) is an…
The ionosphere is a critical component of near-Earth space, shaping GNSS accuracy, high-frequency communications, and aviation operations. For these reasons, accurate forecasting and modeling of ionospheric variability has become…
Operational forecasting of the ionosphere remains a critical space weather challenge due to sparse observations, complex coupling across geospatial layers, and a growing need for timely, accurate predictions that support Global Navigation…
A fundamental limitation of traditional Neural Networks (NN) in predictive modelling is their inability to quantify uncertainty in their outputs. In critical applications like positioning systems, understanding the reliability of…
The ionosphere affects radio signals by altering their speed, direction, and trajectory, causing a temporary delay known as ionospheric delay, which is directly related to the total electron content (TEC). Although research in other…
Many aspects of our societies now depend upon satellite telecommunications, such as those requiring Global Navigation Satellite Systems (GNSS). GNSS is based on radio waves that propagate through the ionosphere and experience complicated…
In this study, we performed a preliminary mapping of Total Electron Content (TEC) over Ecuador using Global Positioning System (GPS) data. This process entails collecting and analyzing pseudorange observations from multiple GPS receivers…
The development of regional services able to provide ionospheric vertical totalelectron content (VTEC) maps and ionospheric indexes with a high spatialresolution, and in near-real-time, are of great importance for both civilianapplications…
The weakly ionized plasma in the Earth's ionosphere is controlled by a complex interplay between solar and magnetospheric inputs from above, atmospheric processes from below, and plasma electrodynamics from within. This interaction results…
In this dissertation is provided a comparative analysis that evaluates the performance of several deep learning (DL) architectures on a large number of time series datasets of different nature and for different applications. Two main…
In this paper, preliminary results from the artificial neural network (ANN) based model developed at IIT Indore has been presented. One year's hourly total electron content (TEC) database has been created from the International Reference…
Most data-driven ionospheric forecasting models operate on gridded products, which do not preserve the time-varying sampling structure of satellite-based sensing. We instead model the ionosphere as a dynamic graph over ionospheric pierce…
The total electron content (TEC) maps can be used to estimate the signal delay of GPS due to the ionospheric electron content between a receiver and satellite. This delay can result in GPS positioning error. Thus it is important to monitor…
The paper presents an assessment of the performances of the global empirical models: International Reference Ionosphere (IRI)-2016 and the NeQuick2 model derived ionospheric Total Electron Content (TEC) with respect to the Navigation with…
Total Electron Content (TEC) and electron density are the basic parameters, which determine the major properties of the Ionosphere. Detail study of the ionospheric TEC and electron density variations has been carried out during geomagnetic…
This paper presents the storm time comparative analysis of the performances of latest versions of global ionospheric models: International Reference Ionosphere (IRI) 2016, NeQuick 2 (NeQ) and the IRI extended to Plasmasphere (IRI-P) 2017…
This paper proposes an extension to conventional regression Neural Networks (NNs) for replacing the point predictions they produce with prediction intervals that satisfy a required level of confidence. Our approach follows a novel machine…
A regression-based model was previously developed to forecast the total electron content (TEC) at middle latitudes. We present a more sophisticated model using neural networks (NN) instead of linear regression. This regional model prototype…