## 4 PVT Results
### Processing of the Collected Data  
In order to apply the developed WE function to the data captured in the project and evaluating its effects into the PVT solution, we use a set of software (SW) commercial tools provided by SSN and developed by Universitat Autonoma de Barcelona (UAB). A sketch of the procedure carried out to obtain the results presented in this section is shown in Figure 12, in which the grey blocks correspond  
Figure 11: Illustration of the phase error computation based on the positioning error. to SW provided by SSN and the white blocks are those developed by UAB. As shown, the first step is to convert the original SBF files provided by SSN to ASCII files, so that the data can be read and processed by MATLAB. Thanks to the modifications of the PVTcalc SW provided by SSN, the outputs of the UAB software must be two different files including corrections and exclusion flags to be applied in the PVT computation. These files are inputs to the PVTcalc SW, which carries out all the needed corrections and modifications to apply the developed algorithms by UAB into the PVT computation. The PVTcalc SW is the proprietary SSN positioning engine and it was derived from the post processing engine of the commercial PP-SDK package [25]. In this paper, we focus on the WE function developed in the FANTASTIC project, so the presented results in this section will be based only on this part of the project. The results about multipath mitigation is out of the scope of this paper. So, the results presented here, only use the WE flags; that is, depending on the RLR of the 2 pol antenna, we will decide whether to exclude the measurement or to apply weighting. This will be decided based on the discrimination between LOS and NLOS conditions. Finally, after applying the developed WE function we have to evaluate the resulting PVT solution. With this aim we have generated a script to compare two different output files. The idea is to compare PVT results such as the RMS 3D error (calculated with a truth reference); percentage of time of each PVT mode, RMS errors for each PVT mode, etc. Before entering into the detailed analysis of the PVT results, let us introduce the general structure and terminology used when analyzing the collected data. The stored I/Q correlation data at each scenario is used to generate the correction and weighting and exclusion files to be fed to the PVTcalc (see Figure 12), thus generating the PVT solution after applying the algorithms. This PVT solution is computed using all the available constellations (i.e., GPS. GLONASS, GALILEO and BeiDou), and then it is compared with the PVT solution obtained without applying the algorithms; that is, the solution using the one antenna configuration. This solution will be referred to as the reference file. Furthermore, the traditional measurements of the GNSS receiver are useful to extract the error statistics of the PVT solutions. For this task the real position of the receiver is of particular importance. For the static scenarios, this position is obtained by averaging the PVT solution among the whole file. Only the RTK fixes are averaged, thus providing a very accurate estimate of the real position. For the dynamic scenario, the real position of the receiver at each time was know thanks to the use of a high-end GPS Inertial Navigation System (INS). This system provides a very accurate position useful to evaluate the positioning error of the gathered data in this scenario. Particularly, the used INS was the commercial product named ATLAS-C of ixblue with specifications given in Ref. [26]. With the real position of the receiver we are able to compare the error statistics of the reference (i.e., one antenna configuration) and the 2 pol-enhanced PVT solution. Specifically, one of these statistics is the total 3D RMS error. This error is computed as the RMS error between the real position (computed  
Figure 12: Sketch of the procedure carried out to obtain the results presented in Section 4.  
as before) and the analyzed PVT solution.