Real-Time Ionospheric Threat Adaptation Using a Space Weather Prediction for GNSS-Based Aircraft Landing Systems

摘要

The use of ground-based augmentation systems (GBASs) is increasing in the national airspace system and also in many nations to support aircraft precision approaches and landing. An anomalous ionospheric event if undetected can cause a potential threat to users of single-frequency-based global navigation satellite system augmentation systems. Current GBAS utilize the pre-defined "worst case" ionospheric threat model in their computation of user position errors to consider all possible ionospheric conditions. This could lead to an excessive availability penalty by adding conservatism on the resulting error bounds. This paper proposes a methodology of real-time ionospheric threat adaptation that adjusts the ionospheric threat model in real time instead of always using the same threat model. This is done by using predicted values of space weather indices for determining the corresponding threat model based on an established relationship between space weather indices and ionospheric threats. Since space weather prediction itself is not reliable due to prediction errors, an uncertainty model was derived from 17 years of historical data. When applied to Category I GBAS in the Conterminous United States, this method lowered the upper bound of the current threat model about 95% of the time during the 17 years (from 1995 to 2011) using the bounded prediction value of the disturbance-storm time index.