Impact of Temporally Correlated Error on ARAIM ISM During Ionospheric Storm Period

Ionospheric delay error is one of the main errors of satellite navigation system. The unstable physical characteristics of ionosphere can severely affect the performance of satellite navigation. Therefore, civil aviation standards require that the impact of ionospheric anomalies (especially ionospheric storms) should be considered in integrity monitoring. To meet the safety requirement of satellite navigation service in civil aviation, it is urgent to analyze the performance of dual-frequency multi-constellation integrity monitoring under stormy condition. In this paper, the empirical model and temporally correlated stochastic error model are used to analyze the ionospheric errors in carrier smoothed code. The Gaussian overbound method is then applied to conservatively represent the error distribution of the temporally corelated stochastic error model. The worst-case overbounding result is used to revise Integrity Support Message (ISM) and evaluate the performance of Advanced Receiver Autonomous Integrity Monitoring (ARAIM) algorithm under stormy condition. The experimental results show that the occurrence of ionospheric storm is able to increase the nominal bias and error variance in ISM and degrade the performance of ARAIM. This study provides an effective method to refine the ISM in ARAIM during ionospheric storm period.