## 4 Results and Discussion
### Static Test  
This section presents the static PCP models for positioning in the static open-sky and complex scenario. Figure 6 shows the HP40 and Mi11 positioning errors in the static open-sky scenario. Figure 6b,c illustrate that for the Mi11 TF-P1I and TF-P1C models, there was a jump in positioning shortly after the start. Upon comparing the results in Table 6, it can be observed that TF-P1I impacts horizontal positioning accuracy, whereas TF-P1C affects U-direction positioning accuracy. This phenomenon may be attributed to a high number of observed BDS-3 triple-frequency data satellites and clock jumps in the second-frequency observation data. It suggests that the quality control method for B2a observations may not be stringent enough. However, the other PCP models, apart from those mentioned above, exhibited consistent positioning performance. The PCP models' positioning root mean square error (RMSE) and improvement percentage compared to SPP are presented in Table 6. Figure 7 shows the PCP models' positioning RMSE in the static scenario. Table 6 and Figure 7a clearly demonstrate that the positioning performance of HP40 exceeded that of Mi11. Additionally, for Mi11, the choice is between B1I or B1C as the ionosphere-corrected pseudo-range did not have a significant impact in the current scenario. For Mi11, there was a slight improvement in U direction positioning accuracy in the IF-P1I and IFUC-P1I models compared to the IF-P1C and IFUC-P1C models. Conversely, the horizontal positioning performance showed a slight improvement in the IF-P1C models and IFUC-P1C models. Figure 5: Flow diagram of PCP processing. Figure 6: Position errors in the static open-sky scenario. (**a**) HP40 positioning errors in IF-P11 and IFUC-P1I models; (**b**) Mi11 positioning errors in IF-P1I and IFUC-P1I models; (**c**) Mi11 positioning errors in IF-P1C and IFUC-P1C models. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Device**} & \multirow{2}{*}{**Model**} & \multicolumn{3}{c}{**RMSE (m)**} & \multicolumn{3}{c}{**Imp**} \\ \cline{3-8}  & & **E** & **N** & **U** & **E** & **N** & **U** \\ \hline \multirow{4}{*}{HP40} & SPP-P1I & 1.76 & 2.17 & 4.33 & / & / & / \\  & DF-P1I & 0.12 & 0.47 & 0.99 & 93.04\% & 78.08\% & 77.08\% \\  & IFUC1P1I & 0.12 & 0.46 & 0.99 & 93.04\% & 78.08\% & 77.08\% \\  & IFUC12 PI1 & 0.13 & 0.46 & 1.00 & 92.97\% & 78.55\% & 77.05\% \\  & SPP-P1I & 1.88 & 2.03 & 4.87 & / & / & / \\  & DF-P1I & 0.30 & 0.34 & 4.33 & 84.09\% & 83.01\% & 11.14\% \\  & TF-P1I & 8.61 & 0.54 & 3.36 & \(-\)357.37\% & 73.50\% & 30.96\% \\ Mi11 & IFUC1P1I & 0.41 & 0.25 & 3.56 & 78.30\% & 87.52\% & 27.02\% \\  & IFUC12 PI1 & 0.24 & 0.38 & 3.96 & 87.42\% & 81.47\% & 18.64\% \\  & IFUC123 PI1 & 0.16 & 0.29 & 3.80 & 91.42\% & 85.61\% & 21.96\% \\  & SPP-P1C & 1.89 & 2.09 & 4.98 & / & / & / \\  & DF-P1C & 0.22 & 0.19 & 4.99 & 88.09\% & 90.91\% & \(-\)0.31\% \\  & TF-P1C & 0.92 & 0.47 & 18.41 & 51.33\% & 77.34\% & \(-\)270.08\% \\ Mi11 & IFUC1P1C & 0.36 & 0.19 & 4.07 & 80.99\% & 90.79\% & 18.20\% \\  & IFUC12 PI1C & 0.20 & 0.28 & 4.39 & 89.60\% & 86.54\% & 11.70\% \\  & IFUC123 PIC & 0.27 & 0.20 & 3.97 & 85.45\% & 90.31\% & 20.16\% \\ \hline \hline \end{tabular}
\end{table} 
Table 6: RMSE results and improvement percentages compared to SPP in the static open-sky scenario. The PCP models, except for TF-P in Mi11, showed significant improvements over SPP. For HP40, the PCP models achieved sub-meter-level accuracy in the east (E) and north (N) directions, and meter-level accuracy in the upwards (U) direction. These improvements represent increases of approximately 92%, 78%, and 77% in each direction, respectively, compared to SPP. Similarly, for Mi11, the PCP models achieved sub-meter accuracy in the E and N directions, and approximately 4-5-m accuracy in the U direction. Compared to SPP, each direction saw an improvement of about 85%, 87%, and 16%, respectively. Figure 8 represents the positioning errors of both HP40 and Mi11 in the static complex scenario.