A Data Fusion Framework for Real-Time GNSS Availability Assessment Under Combined Space Weather and Terrestrial Interference

Global Navigation Satellite Systems (GNSS) have become critical infrastructure for autonomous platforms across space, maritime, and ground domains. Historically, GNSS accuracy degradation was primarily attributed to natural phenomena—ionospheric disturbances, scintillation, and solar activity. However, modern operational environments increasingly face terrestrial threats including intentional jamming, spoofing, and regional denial zones. Current mission planning tools address these risks in isolation, lacking integrated frameworks that assess combined availability under both natural and adversarial conditions.
We present a novel data fusion tool that synthesizes space weather models with Open-Source Intelligence (OSINT) to provide mission planners with predictive GNSS availability assessments. Our approach integrates real-time ionospheric models, solar weather forecasts, and Total Electron Content (TEC) data with crowdsourced jamming reports, regulatory notices and conflict zone intelligence to generate probabilistic availability maps tailored to operational requirements.
The system architecture employs a multi-layer fusion engine: space weather models provide baseline accuracy degradation estimates across orbital geometries and ground locations, while OSINT modules parse structured and unstructured data sources to identify active interference zones. A Bayesian inference framework combines these heterogeneous inputs with mission-specific requirements, position accuracy thresholds, update rates, and operational duration—to produce actionable availability forecasts with quantified uncertainty bounds.
This capability is particularly relevant for Beyond Visual Line of Sight (BVLOS) operations, maritime autonomous surface ships, and deep-space missions where alternative positioning may not be available. By providing mission planners with integrated space-terrestrial threat awareness, the tool enables informed risk management and enhanced operational resilience in GNSS-challenged environments.