Forecasting Thermospheric Density with Transformers for Multi-Satellite Orbit Management

• URL: http://arxiv.org/abs/2511.06105v1
• Date: Sat, 08 Nov 2025 19:02:14 GMT
• Title: Forecasting Thermospheric Density with Transformers for Multi-Satellite Orbit Management
• Authors: Cedric Bös, Alessandro Bortotto, Mohamed Khalil Ben-Larbi,
• Abstract summary: This work presents a transformer-based model that forecasts densities up to three days ahead.<n>It avoids spatial reduction and complex input pipelines, operating directly on a compact input set.<n>It is validated on real-world data and shows potential to support mission planning.
• Score: 41.99844472131922
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Accurate thermospheric density prediction is crucial for reliable satellite operations in Low Earth Orbits, especially at high solar and geomagnetic activity. Physics-based models such as TIE-GCM offer high fidelity but are computationally expensive, while empirical models like NRLMSIS are efficient yet lack predictive power. This work presents a transformer-based model that forecasts densities up to three days ahead and is intended as a drop-in replacement for an empirical baseline. Unlike recent approaches, it avoids spatial reduction and complex input pipelines, operating directly on a compact input set. Validated on real-world data, the model improves key prediction metrics and shows potential to support mission planning.

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