## 3 Signal Quality Assessment
We note that these statistics correspond to the undifferenced level, since they were normalized according to the error propagation law. We also recall that, for such observation combination, the multipath effect is greatly reduced. Table 2 reveals significant divergences of observation noise among the devices, constellations, and frequency bands. As we may read, the employed smartphones are characterized with GPS L1 code noise fitting the range of 0.80 m-3.41 m. Slightly higher precision \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Smartphone**} & \multicolumn{2}{c}{**GPS**} & \multicolumn{2}{c}{**Galileo**} & **BDS** & **GLONASS** \\ \cline{2-7}  & **L1** & **L5** & **E1** & **E5a** & **B1** & **G1** \\ \hline Xiaomi Mi 8 & 1.86 & 0.51 & 1.24 & 0.54 & 1.68 & 4.78 \\ Xiaomi Mi 9 & 3.41 & 0.96 & 2.77 & 0.90 & 2.66 & 5.10 \\ Huawei P 30 & 0.80 & 0.19 & 0.48 & 0.21 & 0.57 & 2.04 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: STD of code noise normalized to undifferenced observations in the units of meters. Figure 4: Histograms of the smartphone L1/E1/B1/G1 code residuals computed as the observations that were double differenced in a time domain. One should note that the GLONASS panel has different axis limits of code residuals when compared to the other panels. We also note an existence of outliers that are included in the outmost bins of code residuals. Figure 3: \(C/N_{0}\) skyplots of GNSS signals collected by Xiaomi Mi 8, Xiaomi Mi 9, and Huawei P30 in left, middle, and right panels, respectively. of observations was obtained for Galileo E1 and BDS B1 bands. On the other hand, STDs for GLONASS code signals were approximately twice of that and fit the range of 2.04-5.1 m, which is also clearly visualized in Figure 4. In Table 2, one can note a significant reduction of the code observation noise for GPS L5 and Galileo E5a frequency bands as compared to L1 and E1 ones, respectively. Such outcomes are coherent with those of high grade receivers, since it was already proved that L5 and E5a code signals exhibit a low observational noise [21]. If we confront the results of particular smartphones, we discover that Huawei P30 outperforms other devices in terms of the code pseudorange precision. Taking GPS L1 signal as an example, we report STD of 0.80 m for Huawei P30, over twice that for Xiaomi Mi 8, and fourfold for Xiaomi Mi 9. Such findings also hold true for other signals and constellations, since Xiaomi Mi 9 always gives the worst, and Huawei P30 always has the best performance in terms of the code noise. To investigate the dependence of the code noise on satellite elevation, we present in Figure 5 the code residuals as a function of the satellite elevation. We recall that these residuals correspond to the observations that were double differenced in time domain. We also note that a 10\({}^{\circ}\) elevation cut-off angle was employed, and the values were averaged in 1\({}^{\circ}\) bins for the clarity of a presentation. In general, the plots show a low elevation dependence of the code noise. For all constellations, Huawei P30 and Xiaomi Mi 8 demonstrate almost an equal level of the code noise over the employed elevation range (10-90\({}^{\circ}\)). The results for Xiaomi Mi 9 exhibit a higher variability; however, we still cannot attribute this effect to the changing elevation angle of the satellite signals. Such findings hold true for all constellations, since in this term we did not notice any significant divergences between GNSS systems. Figure 5: Elevation-dependent quality of code observations on GPS L1, Galileo E1, BDS B1, and GLONASS G1 frequency bands, respectively. Code residuals were computed as the observations that were double differenced in a time domain. The values are averaged over all satellites in 1\({}^{\circ}\) bins. One should note that the GLONASS panel has different axis limits of code residuals when compared to the other panels. In Figure 6, we show the dependence of a code noise on a signal carrier-to-noise density ratio.