<p><strong>Abstract.</strong> The demand for Global Navigation Satellite System in safety-related applications has rapidly increased in the last few years. The foreseeable release of self-driving cars is already showing the importance of the integrity concept of satellite-based navigations. Correction services as EGNOS can actively improve the integrity assurance build up. The paper aims the examination of the EGNOS ionospheric model concerning integrity. The focus is on the Eastern European area are close to the east edge of the EGNOS coverage area. We processed the available EGNOS data from 2018 and compared the performance of the ionospheric correction with a profoundly credible model. The paper presents the basic statistical properties of the comparison focusing on deviances, which could lead to navigation integrity. The article has an additional focus on how the quality of the EGNOS ionosphere model can influence the Protection Level in the eastern region. Satellites with low elevation angle may be out of the EGNOS coverage area, and the absence of these transmitters can negatively affect the Protection Level. The paper shows the quality and quantity of the above mentioned negative impact with the help of real life and simulated data.</p>

The number of devices equipped with global satellite positioning has exceeded seven billion recently. There are a wide variety of receivers regarding their accuracy and reliability. Low cost, multi-frequency units have been released on the market latterly; however, the number of single-frequency receivers is still significant. Since their measurements are influenced by ionospheric delay, accurate ionosphere models are of utmost importance to reduce the effect. This paper summarizes how Gauss process regression (GPR) can be applied to derive near real-time regional ionosphere models using raw Global Navigation Satellite System (GNSS) observations of permanent stations. While Gauss process is widely used in machine learning, GPR is a nonparametric, Bayesian approach to regression. GPR has several benefits for ionosphere monitoring since it is quite robust and efficient to derive a grid model from data available in irregular set of ionospheric pierce points. The corresponding instrumental delays are estimated by a parallel Kalman filter. The presented algorithm can be applied near real-time, however the results are offline calculated and are compared to two high quality TEC map products. Based on the analysis, the accuracy of the GPR modell is in 2 TECu range. The developed methods could be efficiently applied in the field of autonomous vehicle navigation with meeting both accuracy and integrity requirements.