Ionospheric delay is one of the largest and most variable sources of error for Ground-Based Augmentation System (GBAS) users because inospheric activity is unpredictable. Under normal conditions, GBAS eliminates ionospheric delays, but during extreme ionospheric storms, GBAS users and GBAS ground facilities may experience different ionospheric delays, leading to considerable differential errors and threatening the safety of users. Therefore, ionospheric monitoring and assessment are important parts of GBAS integrity monitoring. To study the effects of the ionosphere on the GBAS of Guangdong Province, China, GPS data collected from 65 reference stations were processed using the improved “Simple Truth” algorithm. In addition, the ionospheric characteristics of Guangdong Province were calculated and an ionospheric threat model was established. Finally, we evaluated the influence of the standard deviation and maximum ionospheric gradient on GBAS. The results show that, under normal ionospheric conditions, the vertical protection level of GBAS was increased by 0.8 m for the largest over bound ${\sigma }_{vig}$ (sigma of vertical ionospheric gradient), and in the case of the maximum ionospheric gradient conditions, the differential correction error may reach 5 m. From an airworthiness perspective, when the satellite is at a low elevation, this interference does not cause airworthiness risks, but when the satellite is at a high elevation, this interference can cause airworthiness risks.

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.