# Real-time Precise Point Positioning with a Xiaomi MI 8 Android Smartphone
## 5 Results
The average horizontal RMS positioning error is 0.81m, and the average vertical (up direction) RMS positioning error is 1.65m (using GPS, BDS, and Galileo data). The specific positioning error curves are shown in Figure 6 (panel (a)-(e) for using GPS, BDS, and Galileo data, panel (f)-(h) for using GPS data only). When using GPS, BDS, and Galileo data, after observing for a section of time, the East and North direction errors of all the five time periods can converge to less than 1 m and achieve a relatively stable positioning result; but the U direction positioning result is not stable enough. When using GPS data only, the positioning results are more unstable, and the systematic errors are also greater. The loss of positioning accuracy in the U direction is more obvious compared to the E and N directions. We believe that there are two reasons for the poor performance of single system positioning: the number of satellites observed by mobile phones is not enough, and the quality of smartphone raw GNSS observations is poor. This is consistent with the idea of surveying adjustment: when the accuracy of a single measurement is poor, a large number of repeated observations are needed to improve the overall accuracy. If the number of available satellites continues to increase, the positioning performance may be further improved. However, the GLONASS data of mobile phone seems to contain more gross errors than other GNSS systems, and sometimes it has a bad influence on the positioning results, so we tend to abandon GLONASS data if there are enough visible satellites. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Devices**} & \multicolumn{6}{c}{**RMS of Carrier Phase Observation Change Rates (m/s)**} \\ \cline{2-9}  & **Average** & **GPS L1** & **GPS L5** & **Galileo L1** & **Galileo L5** & **BDS** & **GLONASS** \\ \hline iRTK2 (Geodetic receiver) & 0.021 & 0.021 & \(\backslash\) & 0.021 & \(\backslash\) & 0.021 & 0.022 \\ Huawei Honor 9 & 0.115 & 0.098 & \(\backslash\) & \(\backslash\) & \(\backslash\) & 0.071 & 0.143 \\ Huawei P10 & 0.135 & 0.134 & \(\backslash\) & 0.010 & \(\backslash\) & 0.143 & 0.137 \\ Xiaomi MI 8 & 0.083 & 0.068 & 0.073 & 0.067 & 0.114 & 0.092 & 0.091 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The RMS of carrier phase observation change rates of each mobile phone with different global navigation satellite system (GNSS) systems, where L1 and L5 denote carrier phase observations of two frequencies L1/E1 and L5/E5. Figure 6: The North (N), East (E), and Up (U) direction errors of precise point positioning (PPP) positioning results of the five time periods. (**a**) 1 st time period (G + C + E); (**b**) 2 nd time period (G + C + E); (**c**) 3 rd time period (G + C + E); (**d**) 4 th time period (G + C + E); (**e**) 5 th time period (G + C + E); (**f**) 1 st time period (GPS); (**g**) 2 nd time period (GPS); (**h**) 4 th time period (GPS). The “G”, “C” and “E” denote GPS, BDS, and Galileo. The accuracy of 1 m can meet the needs of most non-professional fields, even some professional fields with low precision requirements [13]. The time required for positioning errors in N and E to both be less than 1 m and the subsequent epoch error to no longer exceed 1 m is counted, as shown in Table 5. 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 indicates that the modified PPP strategy can be applied to real-time positioning and provides a slightly delayed high-precision positioning result. The positioning performance achieved in this work is the best real-time positioning performance that can be achieved with ordinary smartphones until now. We also performed positioning tests using the ordinary PPP strategy which estimates single device time bias and the positioning errors are of the level of several meters.