## 4 PVT Results
### PVT Results Summary  
After showing and analyzing the fine-tuning of the exclusion function for all the considered scenarios, it is time to summarize the best results obtained in each scenario and compare them. Table 3 provides the most important results to evaluate the effects of the developed WE function into the PVT performance. In particular, the second column of the table shows the relative improvement (in terms of RMS 3D error) of using the 2 pol antenna, with respect to the regular configuration (i.e., using 1 antenna). We see how the positioning performance in terms of RMS 3D error is improved with the use of the 2 pol antenna. This improvement is not big in the foliage and dynamic scenarios, a reduction of 3% and 11% of the 3D error, respectively. Nevertheless, this is not the case in the static urban scenario, in which the 2 pol antenna provides a reduction of almost 50% of the original error. The reason of these results can be explained by the type of NLOS propagation in each scenario. It is known that a long delay (distant reflector) introduce a large position error, whereas a short path delay (near reflector) have a much smaller effect. It is likely that the NLOS propagation in the static urban scenario comes from distant reflectors, thus causing large errors. This fact would explain the large improvement in the urban scenario, with respect to the foliage scenario, in which the reflections might come from near reflectors. It is worth pointing out that the presented results were obtained using RTK phase-based positioning, thus providing high-accuracy performance around 5 cm to 2 m for the fixed and float RTK mode, respectively. The percentage of time that the receiver is able to fix the phase ambiguities is shown in the third column of Table 3. The percentage of time in RTK fixed mode is particularly high in the urban scenario, being greater than 80%, and dynamic scenario, which is more than the 50%. The rest of time the receiver is operating in RTK float mode, except in the dynamic scenario in which a 20% of the time the receiver is in code-based positioning mode. This distribution of errors and percentage of time is the reason of the difference of the improvement in terms of RMS error  
Figure 16: Results in the Dynamic scenario for different exclusion thresholds and average configurations. \begin{table}
\begin{tabular}{l c c c c c} \hline \hline \multirow{2}{*}{**Scenario**} & \multirow{2}{*}{**Relative Improvement**} & \multicolumn{3}{c}{**RTK Fixed**} & \multicolumn{2}{c}{**RTK Float**} \\  & & **(\% of Time)** & & **RMS 3D Error (cm)** \\  & & **One Antenna** & **2 pol Exclusion** & **One Antenna** & **2 pol Exclusion** \\ \hline Static Urban & 50\% & 85 & 85 & 80 & 37 \\ Static Foliage & 3\% & 29 & 19 & 213 & 186 \\ Dynamic & 11\% & 61 & 62 & 96 & 88 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison of the results of some parameters for the three considered scenarios: Relative improvement in terms of RMS 3D error, the percentage of time in RTK fixed mode and RMS 3D error in the RTK float mode when applying exclusion or not. between scenarios. Another explanation of these results is the fact that the accuracy of the position solution obtained after excluding signals depends on the quality of the remaining signals and the quality of the user-satellites geometry. For instance, results in Table 3 show how the application of the exclusion function do not improve the percentage of time that the receiver is working with RTK fixed mode, being even worse in the foliage scenario. The reason is that in this scenario, most signals were contaminated by multipath, NLOS reception and/or diffraction. In such a case, when excluding signals, the quality of the remaining signals might be worse than the excluded ones, being thus more difficult for the receiver to fix the phase ambiguities. As a result, in the foliage scenario, those epochs that the receiver is not able to fix the ambiguities become in float mode.