## 3 Characteristics of Xiaomi Mi 8 Raw GNSS Observations
### Pseudorange Observations  
As only a low-cost linear polarized PIF antenna is used in Xiaomi Mi 8, the multipath error is one of the main errors that corrupts the pseudorange observations. For conventional dual-frequency GNSS observations, usually a linear multipath combination is used to characterize the multipath error [20]. However, as to Xiaomi Mi 8, the second frequency L5/E5 is only available on Galileo/QZSS and part of GPS satellites. Therefore, a short baseline experiment as shown in Figure 1 was set to analyze the characteristic of Xiaomi Mi 8 raw pseudorange observations. Single-differenced (SD) measurements between short baseline stations could eliminate the satellite clock errors and greatly weaken the strong spatially-correlated errors (such as the ephemeris error, ionospheric delay, tropospheric delay, etc. ), then SD pseudorange residuals would mainly contain the multipath error and noise of the Xiaomi Mi 8 pseudorange observations [28]. In addition, the pseudorange outlier percentage is also an important indicator to describe the signal characteristic. Regarding the SD pseudorange residuals large than 30 m as outliers, the pseudorange outlier percentage is defined as the ratio of the outlier-corrupted observations on a specific frequency over the total observations on the same frequency. Table 1 gives percentages of Xiaomi Mi 8 pseudorange outliers for different GNSS systems and frequencies over an 8-h period of static data and 2-h dynamic data of track 1. It is seen that for static data, the pseudorange outlier percentages vary from 1.31%-4.79% for GPS, Galileo, and QZSS. It is noted that, for Galileo observations, the percentage of pseudorange outliers is as low as 1.71% and 1.31% for E1 and E5, respectively. In general, the pseudorange outlier rate of L5/E5 observations is significantly lower than that of L1/E1, which means L5/E5 observations may outperform L1/E1 in positioning and navigation. Unexpectedly and for unknown reasons, the percentage of pseudorange outliers is as high as 42.08% and 19.61% for GLONASS and BeiDou, respectively. Therefore, the GLONASS observations are not used in the following positioning experiments. For dynamic data, the pseudorange outlier percentages are much larger than that of static ones; the percentages of pseudorange outliers are mostly about 10% for GPS, Galileo, and QZSS, and rise to 43.86% for GLONASS measurements. Obviously, in a dynamic navigation environment, the quality of raw pseudorange observation from Xiaomi Mi 8 is significantly worsened. Figure 9 illustrates the root mean square (RMS) statistics of the GPS/Galileo/QZSS/BeiDou/ GLONASS L1/E1 and L5/E5 pseudorange SD residuals against C/N0 for the dynamic data. It is noted that the mean RMS of SD residuals for L1/E1 and L5/E5 are as large as 1.5-9 m. This is attributed to the low-cost antenna embedded in Xiaomi Mi 8, whose linear polarization antenna has extremely poor multipath suppression performance. Secondly, the SD residuals for L5/E5 observations are much smaller than those of L1/E1. As BPSK(10) and AltBOC(15,10) modulations are used to modulate Pseudo-Random Noise (PRN) ranging codes onto the L5 and E5 carrier [29], which means \begin{table}
\begin{tabular}{c c c c} \hline \multirow{2}{*}{**Satellite**} & \multirow{2}{*}{**Frequency**} & \multicolumn{2}{c}{**Pseudorange Outlier Percentage (\%)**} \\ \cline{3-4}  & & **Static** & **Dynamic (Track 1)** \\ \hline \multirow{2}{*}{GPS} & L1 & 3.49 & 11.88 \\  & L5 & 1.33 & 9.15 \\ \hline \multirow{2}{*}{Galileo} & E1 & 1.71 & 9.67 \\  & E5 & 1.31 & 5.10 \\ \hline \multirow{2}{*}{QZSS} & L1 & 4.79 & 9.69 \\  & L5 & 3.22 & 6.48 \\ \hline \multirow{2}{*}{GLONASS} & L1 & 42.08 & 43.86 \\ \hline BeiDou & L1 & 19.61 & 23.65 \\ \hline \end{tabular}
\end{table} 
Table 1: Percentages of Xiaomi Mi 8 pseudorange outliers for different navigation systems and frequencies.