## 3 Results  
### Positioning Performance of the Single Systems  
In order to analyze the positioning accuracy and convergence time performance of a single system, we obtain the corresponding quantile by using data from each tracking station for each system for a month in static or kinematic mode to plot the boxplot. Figure 5 illustrates the monthly convergence time and RMS of static PPP based on the three single-system schemes, and the month median RMS and convergence time are also indicated. Here, we define \"convergence\" as obtaining a 3D-positioning error less than the predefined threshold at the current epoch and the following 20 epochs, which has been adopted from [PERSON] and [PERSON] (2018). Only when the positioning errors of all 20 epochs are within the threshold do we consider that the position has converged at the current epoch. Here, the threshold is 1 dm, which has been suggested by [PERSON] et al. (2018). For positioning accuracy (RMS), it is calculated through the same convergence period; here, we have chosen 2 h after the start of PPP filtering for each test. In order to facilitate the analysis, the east and north component vectors are synthesized as the horizontal component, and the up component is taken as the vertical component. For the convergence time in the horizontal component, GPS-only has the least convergence time of static PPP solutions, about 10.9 min. The performance of the remaining two single systems is not as good as GPS-only. Specifically, Galileo-only performs better than BDS-3-only, with values of about 16.5 min, and it is 20.4 min for BDS-3-only. Similar to the horizontal component, GPS-only has the shortest convergence time in the vertical component, which is 11.0 min for static PPP. With convergence times of about 16.5 min, BDS-3-only outperforms Galileo-only, which has values of roughly 17.0 min for static PPP. As shown in the figure, the RMS of both PPP solutions in the horizontal component is vastly better than in the vertical component. The median RMS values for GPS-only are 0.39 and 1.00 cm; they are 0.57 and 1.03 cm for Galileo-only. We can see that the RMS of GPS-only and Galileo-only in the static PPP solution are comparable. However, the median RMS of PPP solutions for BDS-3-only is larger than that of the other two single-system schemes, where the values are 0.86 and 1.55 cm in the horizontal and vertical components, respectively. Figure 4: Distribution of the number of visible satellites and PDOP values for different systems (G is short for GPS, E is short for Galileo, CM is short for BDS-3 MEO, and CMI is short for BDS-3 MEO+IGSO) over a day (1 September 2022) with an elevation cut-off of 7\({}^{\circ}\). For different solutions, as is generally known, the accuracy of kinematic PPP is obviously lower than that of static PPP due to the weaker model. Meanwhile, the performance of different single systems is compared. Similar to Figure 5, Figure 6 shows the distribution of the convergence time and RMS of the kinematic PPP. Each panel in Figure 6 depicts the static and kinematic PPP convergence times using three single systems in the horizontal and vertical components, respectively. In contrast to the RMS performance, the convergence time of both PPP solutions, except Galileo, in the vertical component is shorter than in the horizontal component. For the horizontal component, GPS-only has the least convergence time of the kinematic PPP solutions, about 21.9 min. Galileo-only performs better than BDS-3-only, with values of about 27.5 min, whereas it is 32.0 min for BDS-3-only. Similar to the horizontal component, GPS-only has the shortest convergence time, which is 17.0 min. With convergence times of about 31.0 min, BDS-3-only outperforms Galileo-only, which has values of roughly 35.5 min. The median RMS for GPS-only is 2.30 and 3.83 cm, and the median RMS of the PPP solutions for Galileo-only and BDS-3-only is twice as large as GPS-only, with a value of 4.75 and 7.07 cm for Galileo and 4.73 and 7.62 cm for BDS-3 in the horizontal and vertical components, respectively.