4.3.2. Ambiguity Fixing Rate

The ambiguity fixing rate of GPS, GLONASS, and GPS+GLONASS modes of the three networks is listed in Table 7. GPS has the lowest ambiguity fixing rate in the middle latitude network but the highest ambiguity fixing rate in the low latitude network. As there is no obvious difference in the GPS positioning accuracy of the three networks, we analyzed the types of receivers used. The receivers of the high latitude network were of 3 brands and 5 models, the receivers of the middle latitude network were of 3 brands and 6 types, while in the low latitude network, there were only 2 brands and 2 models receivers. This suggests that the different levels of ambiguity fixing rate could be related to the number of receiver types used in different networks. The different signal distortion biases between inhomogeneous receivers affect the GNSS data processing [31,32]. Despite having the best receiver homogeneity, the ambiguity fixing rate of GLONASS in the low latitude network was only 26.4%, but 74.7% for GPS.

**Table 7.** The ambiguity fixing rate of DD processing (G, R, and G + R in black body denote the data processing mode, respectively. No bold G, R, and G + R represent the ambiguity fixing rate of GPS+GLONASS processing mode, respectively).


#### 4.3.3. Tropospheric Estimates

Taking IGS tropospheric products as the reference value, the differences between the estimated ZTDs and the IGS products were calculated. The stations SOD3, WTZR, and SPTU were also used to illustrate the estimation accuracy of three different positioning modes. The ZTD errors are presented in Figure 10. The data gaps in Figure 10 were caused by missing observations or the reference data. It can be seen that the ZTD estimates present wider discrepancies as the latitude decreases.

**Figure 10.** The ZTD error series of station SOD3, WTZR, and SPTU estimated with DD processing.

The RMSE of all the stations is shown in Figure 11. The mean RMSE of each network and their comparison between different processing modes are shown in Table 8.

**Figure 11.** The RMSE of ZTDs estimated with DD processing.

**Table 8.** The mean RMSE of ZTDs estimated with DD processing for each network and their comparison between different processing modes (The positive red and negative green values indicate the percentage increment and reduction of accuracy, respectively).


The statistical results show that, in all the three networks, the ZTD estimates of GLONASS are obviously worse than that of GPS, which are 15.85%, 12.26%, and 32.24% lower in the high, middle, and low latitude networks, respectively. The accuracy of GPS+GLONASS in the high latitude network is 2.08% worse than that of GPS but slightly better in the middle and low latitude networks, about 1.06% and 4.00%, respectively. The consistency between the estimated results and the IGS products decreases as the latitude decreases for GPS, GLONASS, and GPS+GLONASS.

#### *4.4. Static PPP Results*

The positioning accuracy, the convergence time, and the accuracy of ZTD estimates with the PPP processing strategy are analyzed.

#### 4.4.1. Positioning Accuracy

Taking IGS daily coordinates as the reference value, the coordinate difference between the estimated coordinates with PPP and the IGS daily coordinates was calculated. The coordinate error series of GPS, GLONASS, and GPS+GLONASS modes on N, E, and U components of SOD3, WTZR, and SPTU are shown in Figure 12.

**Figure 12.** The coordinate error series of station SOD3, WTZR, and SPTU estimated with PPP.

As shown in Figure 12, the GLONASS coordinate error series of SOD3 is as steady as that of GPS, while the coordinate error of WTZR and SPTU estimated with GLONASS observations is much more dispersed than other estimate modes. In addition, the magnitude of the error series on U components of three positioning modes at the SPTU station is larger than at the other stations.

The RMSE of N, E, and U components, together with the 3D RMSE for all the stations, are shown in Figure 13. The mean RMSE of N, E, and U components, together with the 3D RMSE for each network, are calculated and listed in Table 9.

**Table 9.** The mean RMSE of coordinates for each network estimated with PPP and their comparison between different processing modes (The positive red and negative green values indicate the percentage increment and reduction of accuracy, respectively).


**Figure 13.** The RMSE of coordinates of all the stations estimated with PPP.

Figure 13 and Table 9 illustrate the RMSE of coordinates estimated with PPP. The GLONASS estimated coordinates have comparable accuracy with GPS in the high latitude network. The accuracies on N and E components are 13.62% and 0.87% better than that of GPS, but the accuracies on U and 3D components are 2.83% and 1.37% worse than that of GPS. GPS+GLONASS presents the best coordinate estimates in the high latitude network. The percentages of improvement over GPS on N, E, and U components are 18.78%, 10.37% and 7.87%, respectively, and the 3D positioning accuracy is 9.35% better than that of GPS. GPS stand-alone mode presents the best coordinate estimates except for the E component in the middle latitude network. The coordinate accuracy on the E component of combined GPS+GLONASS constellations has an advantage of 2.99% over GPS. The accuracies of GLONASS on N, E, and U components are worse than that of GPS, at 19.83%, 21.77%, and 20.40%, respectively. The 3D positioning accuracy of GPS+GLONASS is 1.52% lower than that of GPS. GLONASS shows the worst coordinate estimates among the three positioning modes in the low latitude network. The 3D positioning accuracy is 7.58% lower than that of GPS; however, the 3D positioning accuracy improvement of GPS+GLONASS is 11.40% over GPS. The positioning performance of PPP with different modes in different latitudes is basically consistent with that of the DD network solutions.

#### 4.4.2. Convergence Time

The convergence time performance of GPS, GLONASS, and GPS+GLONASS processing modes was studied. The criterion of convergence is achieving a positioning error of less than 1 decimeter on N, E, and U components. The mean convergence time for each station is shown in Figure 14. The mean convergence time for each network is listed in Table 10. The results clearly show that the convergence time of GLONASS PPP is distinctly longer than that of GPS, and the increased percentages are 51.90%, 45.28%, and 105.30% in the high, middle, and low latitude networks, respectively. Compared with GPS PPP, GPS+GLONASS processing reduces the convergence time, and the shortened percentages are 6.11%, 16.57%, and 14.60% in the high, middle, and low latitude networks, respectively. The convergence time gets longer as the latitude decreases for GPS, GLONASS, and

GPS+GLONASS positioning modes, and the convergence time of GLONASS in the low latitude network is obviously longer, up to 49.83 minutes.

**Figure 14.** The convergence time of PPP.

**Table 10.** The mean convergence time of PPP for each network and their comparison between different processing modes (The red values indicate the percentage reduction of convergence time and the green values indicate the percentage increment of convergence time).


#### 4.4.3. Tropospheric Estimates

The differences between the estimated ZTDs with PPP after convergence and the IGS products were calculated to obtain the time series and the RMSE of ZTDs. Figure 15 shows the ZTD error series of station SOD3, WTZR, and SPTU. The RMSE of all the stations is shown in Figure 16. The mean RMSE of ZTDs for each network and their comparison between different processing modes are shown in Table 11.

**Figure 15.** The ZTD error series of station SOD3, WTZR, and SPTU estimated with PPP.

**Figure 16.** The RMSE of ZTDs estimated with PPP.

**Table 11.** The mean RMSE of ZTDs estimated with the PPP of each network and their comparison between different processing modes (The positive red and negative green values indicate the percentage increment and reduction of accuracy, respectively).


Figure 15 shows that the ZTD estimates are dispersed as the latitude decreases. From Figure 16 and Table 11, we can see that the ZTD estimates of GLONASS are less accurate than that of GPS in all three networks, which are 10.10%, 6.82%, and 14.08% lower in the high, middle, and low latitude networks, respectively. The addition of GLONASS will improve the accuracy of tropospheric estimates, and the accuracy improvements are 5.19%, 6.98%, and 7.79% in the high, middle, and low latitude networks, respectively. The accuracy of estimated ZTDs decreases as the latitude decreases for GPS, GLONASS, and GPS+GLONASS.
