Parametrization and Prediction of EGNOS GIVD values

Abstract

Global Navigation Satellite Systems (GNSS) enable positioning almost everywhere in the world under open-sky conditions. However, the GNSS-based position is not exact due to various error sources. Errors in range measurements caused by the ionospheric delay are the largest error source in positioning with consumer grade receivers. In this paper we propose an approach for predicting the ionospheric delay for such receivers. Our method models the ionosphere by a predefined set of trigonometric basis functions, whose coefficient are predicted using a Kalman filter (KF). For the KF we introduce a new, Klobuchar-based state model, which outperforms a standard, random walk state model in our tests with real-world data for various filter update intervals. Our tests show, furthermore, that European Geostationary Navigation Overlay Service (EGNOS) transmissions can be parameterized and predicted without significant information loss, which reduces the amount of data that has to be transmitted to the receiver.