Year: 2025
Type: conference-paper
Abstract: Accurate prediction of ionospheric parameters in four-dimensional spatiotemporal domains (time, longitude, latitude, and altitude) is critical for mitigating space weather ionospheric effects and ensuring robust GNSS operations.Extreme ionospheric disturbances caused by solar magnetic storms, significantly impact the performance and reliability of Global Navigation Satellite Systems (GNSS).With rapid development of machine learning, this study addresses the challenge of ionospheric modeling and prediction by introducing a novel deep learning-based data assimilation framework: the Deep Operator Network (DON) model for four-dimensional ionospheric parameter forecasting.
Authors: Haiyang Fu, Dijia Cai, Zitong Wang
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4414165565
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