# Real-time Precise Point Positioning with a Xiaomi MI 8 Android Smartphone
## 6 Conclusion and Discussion  
In this paper, we compared and analyzed the quality of GNSS raw observations of different smartphones. Using a modified single-frequency PPP strategy, a real-time high precision smartphone positioning is achieved. Taking the geodesic receivers' carrier phase observations as the standard values, the average RMS of the pseudorange observations of Huawei Honor 9, Huawei P10, and Xiaomi MI 8 smartphones are 12.23 m, 8.58 m, and 3.97 m, respectively. The average RMS of the carrier phase observation change rates of these three smartphones are 5.5, 6.4, and 4.0 times of the geodetic receivers, respectively. As the world's first dual-frequency GNSS smartphone, the quality of the GNSS raw observations of the Xiaomi MI 8 smartphone is greatly improved compared to the ordinary single-frequency smartphones. In the L1/E1 band, the Xiaomi MI 8 smartphone has smoother pseudorange and carrier observations, and meanwhile the raw observations of the L5/E5 band are even better. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & \multicolumn{8}{c}{**RMS Positioning Errors (m)**} \\ \cline{2-10}
**Time periods** & \multicolumn{2}{c}{**GPS**} & \multicolumn{2}{c}{**BDS**} & \multicolumn{2}{c}{**G + C**} & \multicolumn{2}{c}{**G + C + E**} & \multicolumn{2}{c}{**G + C + E + R**} \\ \cline{2-10}  & **U** & **H** & **U** & **H** & **U** & **H** & **U** & **H** & **U** & **H** \\ \hline
1 st & 2.56 & 1.92 & 7.77 & 3.28 & 2.19 & 0.89 & 2.24 & 0.89 & 2.28 & 1.05 \\
2 nd & 5.25 & 2.92 & 2.41 & 3.94 & 1.65 & 0.77 & 1.47 & 0.76 & 1.39 & 0.56 \\
3 rd & 5.33 & 2.84 & 6.59 & 4.11 & 1.37 & 0.67 & 1.33 & 0.68 & 1.39 & 0.72 \\
4 th & 10.54 & 3.86 & 9.69 & 4.80 & 1.99 & 0.85 & 1.86 & 0.85 & 1.16 & 0.79 \\
5 th & 6.15 & 3.54 & 18.77 & 5.78 & 1.65 & 0.87 & 1.35 & 0.88 & 2.14 & 0.76 \\ Average & 5.97 & 3.02 & 9.05 & 4.38 & 1.77 & 0.81 & 1.65 & 0.81 & 1.67 & 0.78 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The RMS positioning errors of the five time periods using different global navigation satellite systems (GNSS) system combinations. The “G”, “C”, “E” and “R” denote GPS, BDS, Galileo and GLONASS. The “U” and “H” denote “up” and “horizontal”. \begin{table}
\begin{tabular}{c c} \hline \hline
**Time Periods** &
\begin{tabular}{c} **Time Required for Positioning Errors in N and E** \\ **Directions to Be Less than 1 m (s)** \\ \end{tabular} \\ \hline
1 st & 26 \\
2 nd & 25 \\
3 rd & 11 \\
4 th & 2 \\
5 th & 3 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: The time required for positioning errors in N and E directions less than 1 m of all time periods. By analyzing the GNSS raw observations, it is found that all the three smartphones tested have the phenomenon that the differences between pseudorange observations and carrier phase observations are not fixed. This may be a general problem with smartphones that needs to be modified in the positioning algorithm. Using the real-time single-frequency PPP positioning strategy which estimated double clock biases of smartphone, the results show that using more GNSS systems data can effectively improve positioning performance, but GLONASS data sometimes have a bad effect on positioning performance. In the case of using GPS, BDS, and Galileo data, the horizontal and vertical RMS positioning error of 0.81 and 1.65 m on average are achieved with a Xiaomi MI 8 smartphone. The time required for positioning errors in N and E directions to be under 1 m of each time period is less than 30 s, which is the best real-time positioning performance that can be achieved with smartphones. Compared with the experimental results of [PERSON] et al. [13] who conducted similar studies, their positioning accuracy is better than our work (the average horizontal RMS positioning error after convergence less than 0.30 m). However, because we used single-frequency data, the ionospheric errors could not be effectively eliminated, and the predicted IGS products used were predicted products (for real-time positioning), so the difference in accuracy is acceptable.