## 4 Experiment and Result
### Multi-GNSS Kinematic PPP Solution  
The same set of GNSS data observed by the Huawei Mate30 was used for kinematic positioning with the two PPP methods described above. Unlike the static PPP method, the receiver position and corresponding error covariance should be initialized per epoch in the process of kinematic PPP, and the receiver position initialized from SPP which is estimated using the pseudorange on the L1 frequency with a variance of 60\({}^{2}\) (m\({}^{2}\)). Moreover, it should be noted that the receiver clock should be initialized with a variance of 60\({}^{2}\) (m\({}^{2}\)) per epoch both in static and kinematic PPP, and other parameters such as ambiguity are usually initialized at the beginning, which is the same as static PPP. The kinematic \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{3}{*}{**Direction**} & \multicolumn{8}{c}{**Static Precise Point Positioning Error RMS (m)**} \\ \cline{2-9}  & \multicolumn{8}{c}{**Huawei Mate30**} & \multicolumn{8}{c}{**Geodetic Receiver**} \\ \cline{2-9}  & **G(EK)** & **G(CR)** & **GB(EK)** & **GB(CR)** & **GBR(EK)** & **GBR(CR)** & **SF** & **DF** \\ \hline
10 min & & & & & & & & \\ E & 0.520 & 0.298 & 0.207 & 0.221 & 0.095 & 0.273 & 0.341 & 0.129 \\ N & 0.701 & 0.594 & 0.221 & 0.533 & 0.614 & 0.387 & 0.567 & 0.114 \\ U & 4.645 & 2.352 & 2.954 & 2.081 & 3.432 & 1.302 & 1.119 & 0.580 \\
3D & 4.726 & 2.444 & 2.969 & 2.160 & 3.488 & 1.386 & 1.300 & 0.605 \\
100 min & & & & & & & & \\ E & 0.183 & 0.160 & 0.150 & 0.125 & 0.085 & 0.188 & 0.207 & 0.056 \\ N & 0.293 & 0.253 & 0.160 & 0.207 & 0.276 & 0.165 & 0.323 & 0.037 \\ U & 1.850 & 0.878 & 1.333 & 0.817 & 1.545 & 0.761 & 0.478 & 0.205 \\
3D & 1.882 & 0.928 & 1.351 & 0.852 & 1.572 & 0.801 & 0.613 & 0.216 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: RMS of GPS, GPS/BDS, and GPS/BDS/GLONASS static PPP errors of the Huawei Mate30 and geodetic receiver. 3D denotes three-dimensional. Figure 7: Comparison of the RMS of static PPP errors with respect to GPS, GPS/BDS, and GPS/BDS/GLONASS observed by the Huawei Mate30 in 10, 60, and 100 min. The RMS of single frequency and dual frequency PPP errors of the geodetic receiver during the same time period is presented for comparison. GEO denotes geodetic receiver; SF and DF denote single frequency and dual frequency, respectively. positioning biases of different combinations of GPS, BDS, and GLONASS in three directions are shown in Figure 8.  
From Figure 8, although the maximum error of GPS in three directions is significantly reduced, it can be observed that there are still some large variations in GPS(CR), and the maximum three-dimensional error of GPS(CR) still reaches 17.442 m. The reason for this may be attributed to the residuals of many satellites, which are outliers and difficult to eliminate in the process of iteration. Therefore, with validity of sufficient observations, the maximum three-dimensional errors of GPS/BDS(CR) and GPS/BDS/GLONASS(CR) reduce to 11.083 and 10.317 m, respectively. Moreover, it can be seen that there is no obviously convergent pattern in the kinematic PPP error series in Figure 8, which is different from that of the geodetic receiver. It may be caused by the high code noise and limited to terms of both quality and quantity of L5 observations, which further affect the convergence of kinematic PPP. Compared with the positioning error between GPS(EK) and GPS(CR), the RMS of GPS(CR) kinematic PPP error in east and north direction is similar to that of GPS(EK), but the proposed algorithm still outperforms the conventional one in two aspects, one is that the horizontal maximum error was reduced from 20.899 m for GPS(EK) to 7.422 m for GPS(CR) and the other is that RMS of vertical positioning error decreases from 4.162 m for GPS(EK) to 2.235 m for GPS(CR). Meanwhile, it can be observed that there is a significant reduction in maximum error of horizontal and vertical for GPS/BDS/GLONASS based on the proposed PPP method.