# A GNSS-Cellular Network Hybridization Strategy for Robust Positioning
## 2 Materials and Methods
### Study Area and Observation Data  
The performance of the proposed positioning methods was evaluated through a series of experiments conducted in three distinct environmental scenarios:  
* Outdoor: A rooftop location with an unobstructed line of sight (LoS) to GNSS satellites. * Urban canyon: An area surrounded by buildings approximately 24 m in height, with dense vegetation present. * Indoor: A location inside a building, situated near a window to allow partial signal reception. For the outdoor and urban canyon scenarios, highly accurate reference coordinates were obtained using a Leica System 1200 professional-grade GNSS receiver operating in real-time kinematic (RTK) mode. In the indoor scenario, where a GNSS was not reliably available, a Trimble C5 Total Station was used to establish reference positions with a centimeter-level accuracy. BS positions covering the test area were identified using publicly available datasets from Spain's national telecommunications authority [35]. To ensure positional accuracy, these coordinates were verified in the field using the Trimble C5 Total Station. Figure 1 provides an overview of the experimental setup. The exact coordinates of the mobile network BSs and reference points are listed in Tables 1 and 2, respectively. In each of the three environments (see Figures 2-4), observational data were collected for both GNSS and 4G mobile networks using two Android-based applications:  
* Geo++ RINEX Logger for recording RINEX files. * CellTracker for collecting 4G cellular and GNSS-based position coordinates (\(\mathsf{x}\), \(\mathsf{y}\), \(\mathsf{z}\)). \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Scenarios** & **E (m)** & **N (m)** & **U (m)** & \(\mathbf{\sigma_{E}}\) (m)** & \(\mathbf{\sigma_{N}}\) (m)** & \(\mathbf{\sigma_{U}}\) (m) \\ \hline Outdoor & 729,010.11 & 4,373,590.06 & 72.98 & 0.03 & 0.02 & 0.04 \\ Urban canyon & 729,063.61 & 4,373,540.17 & 55.07 & 0.01 & 0.03 & 0.05 \\ Indoor & 729,034.20 & 4,373,567.76 & 60.58 & 0.02 & 0.02 & 0.05 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Reference point coordinates and associated standard deviations. Both applications operated simultaneously in the background without interference (see Appendix A and Figures A1 and A2 for CellTracker technical details). Since the positioning data from the mobile network were accessed through official APIs and not derived from low-level radio measurements, signal strength maps and Doppler shifts were neither collected nor modeled in this study. Data collection was conducted in static mode, during which the UE--a Xiaomi Mi8 Pro smartphone--recorded both GNSS and 4G signals. However, due to the limited availability of nearby 5G BSs in the study area, only 4G observations were used for the evaluation. The original data files used in the experiments are included as Supplementary Materials. The  
Figure 1: Geographic positions of the BSs and UE locations for the outdoor, indoor, and urban canyon scenarios. Figure 2: UE—Xiaomi Mi 8 Pro smartphone—positioned on a rooftop in the outdoor scenario. observation period for each static test lasted 10 min, during which positioning data were continuously collected at 15 s intervals. Although the GNSS pseudorange data were recorded continuously at a 1 Hz rate using the Geo++ RINEX Logger, the network-based data obtained via the CellTracker app showed irregularities, including missing entries and variable intervals between measurements. To ensure temporal consistency and data reliability, we selected one valid measurement every 15 s. This sampling rate was chosen deliberately to reflect the static nature of the acquisition setup, where the UE remained stationary throughout each test. The selected interval is therefore suitable for emulating periodic low-rate monitoring conditions rather than high-frequency dynamic tracking scenarios. Figure 4: UE—Xiaomi Mi 8 Pro smartphone—positioned near a window in the indoor scenario. Figure 3: UE—Xiaomi Mi 8 Pro smartphone —in the urban canyon scenario.