Signal-In-Space User Range Errors (SIS UREs) are assumed to be overbounded by a normal distribution with a standard deviation represented by the User Range Accuracy (URA). The BeiDou Navigation Satellite System (BDS) broadcast URA is not compatible with the historical SIS URE performance that affects the Advanced Receiver Autonomous Integrity Monitoring (ARAIM) False Alert Probability (Pfa) and availability evaluation. This study compares the BDS broadcast and precise ephemeris from 1 March 2013 to 1 March 2017 to obtain SIS UREs. Through analyzing the statistical characteristics of the SIS UREs, we obtain the standard deviation σ_URE for the accuracy and continuity and σ_URA used for the integrity of the SIS UREs. The results show that the broadcast σ_URA of 2 m cannot completely overbound SIS UREs for all BDS satellites, but the σ_URA of 2.4 m can. Then, we use the σ_URA of 2.4 m to evaluate the ARAIM Pfa and availability. The results show that the Pfa may increase to 2 × 10⁻⁵ and exceed its limit by an order of magnitude. We also consider the differences between the SIS UREs of Geostationary Earth Orbit (GEO), Inclined Geo-Synchronous Orbit (IGSO), and Medium Earth Orbit (MEO). The results indicate that all Pfa values calculated by the computed σ_URE are less than the Pfa in the Integrity Support Message (ISM) for the worst-performing GEO satellite. The approximately 55% Pfa calculated by the computed σ_URE is less than the Pfa in ISM for the worst-performing IGSO satellite. Most Pfa values calculated by the computed σ_URE is less than the Pfa in the ISM for the worst-performing MEO satellite. For BDS satellites, the Pfa is mainly affected by σ_URE. When the σ_URA of 2.4 m is used to evaluate the availability, the computed availability is lower than the availability calculated by the broadcast σ_URA/σ_URE and the greatest degradation can reach 25%.

Under abnormal troposphere, Ground-Based Augmentation System (GBAS) is unable to eliminate troposphere delay, resulting in non-nominal troposphere error. This paper analyzes the troposphere meteorological data of eight International GNSS Monitoring Assessment System (iGMAS) stations and 10 International GNSS Service (IGS) stations in China and records the most serious conditions during 2015 and 2016. Simulations show that the average increase in Vertical Protection Level (VPL) of all visible satellites under non-nominal troposphere is 2.32 m and that more satellites increase the VPL. To improve GBAS integrity, this paper proposes a satellite selection method to reduce the non-nominal troposphere error. First, the number of satellites in the optimal subset is determined to be 16 based on the relationship among VPL, non-nominal troposphere error and satellite geometry. Second, the distributions of the optimal satellites are determined. Finally, optimal satellites are selected in different elevation ranges. Results show that the average VPL increase caused by non-nominal troposphere error is 1.15 m using the proposed method. Compared with the brute method and greedy method, the running rate of the proposed method is improved by 390.91% and 111.65%, respectively. In summary, the proposed method balances the satellite geometry and non-nominal troposphere error while minimizing the VPL and improving the running rate.

The Satellite-based augmentation system (SBAS) is intended to provide real-time differential global navigation satellite system corrections with the high accuracy, availability, and integrity required for aviation applications. Since the performance of Satellite clock and ephemeris (SCE) corrections and Ionospheric range delay (IRD) corrections can vary dramatically depending on satellites and Ground reference stations (GRSs) geometry, therefore, we present a GRSs distribution optimized criteria and process to improve SBAS corrections performance. The present step-by-step optimized scheme using the average satellite surveillance dilution of precision and relative centroid metric availability of grid points as fitness values to determine the appropriate GRSs distribution to sufficiently meet the corrections requirements. The results show that the statistical mean RCM availability can reach more than 0.5518 for all IGPs and the coverage depth of GRSs in China and its surrounding areas is more than 25, which fully satisfies the requirement for solving SCE and IRD corrections.