LAUSR

Integrity monitoring of global navigation satellite systems (GNSSs) is designed to protect against extremely rare hazardous events, characterized by an integrity risk with a very low probability. The traditional integrity risk evaluation is restricted simultaneously by non-Gaussian measurement errors and impractical time consumption. Based on extreme value theory, a generalized Pareto distribution (GPD)-based integrity risk evaluation method in the position domain is proposed to estimate the upper bound of the integrity risk. In order to account for the GPD modeling error and estimation error, conservatism of the proposed GPD-based integrity risk evaluation is obtained by imposing model-driven and data-driven overbounding. Simulation results from four typical heavy-tailed distributions have shown that conservative and tight bound integrity risk results can be achieved. Furthermore, real-world European Geostationary Navigation Overlay Service measurements experiment has shown that the integrity risk evaluation resulting from the proposed method is at least one order less than the traditional evaluation method, which is consistent with official publications.