## 4 Field Test Results and Discussions  
Field observations were processed using the RTKLIB for the SPP and RTK methods. For the RTK/INS fusion results, a separate custom software framework was used. This framework integrates GNSS data with INS measurements to enhance the positioning accuracy. We ensured that the quality control methods in our custom software aligned with those used in RTKLIB to make the results comparable. Specifically, both systems employ similar outlier detection and correction mechanisms. While the RTKLIB was used for the SPP and RTK processing, the RTK/INS fusion results were obtained using a custom software framework designed to integrate the GNSS and INS data effectively. We acknowledge that using different software for these processes could introduce variations due to differing quality control methods. However, we have aligned the quality control  
Figure 3: The vehicle’s path while logging measurements using smartphones and the U-Blox receiver (**a**). (**b–e**) Field photos of the 4 selected parts of paths 1, 2, 3, and 4 in (**a**), respectively. procedures between the RTKLIB and our custom software to ensure that the results are directly comparable. This approach allows us to leverage the strengths of each processing method while maintaining consistency in the data quality assessment. Next, the results are compared with the RTK/INS fusion method for two smartphones, the Xiaomi Mi 8 and Samsung S21 Ultra, using the U-Blox ZED-F9R receiver model. A sample case analysis was conducted on four segments of the overall vehicle trajectory. Figure 4 illustrates the trajectories of the results of three different methods, SPP, RTK, and RTK/INS fusion, respectively, on four streets, Daneshgah, Peighambarieh, Naderi, and Khorramshahr. The figures on the right (i.e., b, d, f, and h) show the results of the Mi 8, and the figures on the left (i.e., a, c, e, and g) show the results of the S21 Ultra. Also, Tables 2 and 3 compare the horizontal error of the positioning results with the S21 Ultra and Xiaomi Mi 8 smartphones from the three SPP, RTK, and fusion methods with the U-Blox receiver. The first selected street, Daneshgah, is a pretty wide street with low- and medium-sized buildings and an appropriate sight of the horizon. As expected, the street shows the lowest RMS values among other streets in both smartphones and for all methods. The RMS value in the fusion method compared to RTK mode was reduced by 74%, decreasing from 1.477 m to 0.380 m for the Xiaomi Mi8 smartphone. Likewise, there was a decline of 77% in the figure for the Samsung S21 Ultra, decreasing from 1.83 to 0.415. Compared to the SPP mode, the RMS from the fusion method value declined by 91% for the Xiaomi Mi8 smartphone, decreasing from 4.242 m to 0.380 m. In a similar trend, for the Samsung S21 Ultra, the RMS value for the SPP mode experienced a reduction of 92.8%, decreasing from 1.833 m to 0.415 m (Figure 5). It is worth noting that the RMS values of the RTK mode were smaller than those of the SPP mode for both smartphones. The SPP mode was less accurate than the RTK mode, which is expected, since SPP positioning typically uses signals from a single GNSS satellite constellation without corrections for atmospheric interference or other errors. The fusion method improved the SPP mode for both phones, which suggests that integrating data from additional sensors or systems (like IMUs or even other satellite constellations) can significantly enhance the positioning accuracy. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**St.** & **RTK (m)** & **SPP (m)** & **Fusion (m)** \\ \hline Daneshgah & 1.477 & 4.242 & 0.380 \\ Khorramshahr & 2.826 & 7.221 & 0.446 \\ Naderi & 15.638 & 6.240 & 1.518 \\ Peighambarieh & 9.805 & 4.484 & 1.188 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison of the horizontal error of the positioning results with the Mi 8 smartphone from the three SPP, RTK, and fusion methods with the U-Blox receiver.