# Analysis of the Impact of Multipath on Galileo System Measurements
## 4 Multipath Analysis  
The experiment was conducted using observations captured by two stations, located on the roof of the Main Building of the Warsaw University of Technology: WUT1 and WUT2, 4.75 m apart. Both stations are located in a typical environment for reference stations. Measurements were recorded using Septentrio PolaRx5 receivers connected to a Leica Choke-Ring AT504 antenna at WUT1 and a Septentrio PolaNt ChokeRing B3/E6 at WUT2 (see Figure 1). GPS and Galileo raw data collected on 29 June 2018 (180 DOY) at 1 Hz rate were used. There have not been many changes in the GPS and Galileo constellations since then, so the results obtained can be considered up-to-date. The types of observations analyzed here are summarized in Table 1. The signals analyzed include Galileo signals on all available civilian frequencies and band E6. All observations concern pilot channels without navigation data. For GPS, a C/A code, a signal on the L5 frequency (also in the form of a pilot channel) as well as two observations on the L2 frequency: a civilian signal L2C(L) (long code of the pilot channel) and an observation of a precise P code, using the Z-tracking method (L2W), were recorded. The multipath effect for code observations was determined using CMC combination. On the basis of Equation (9), combinations for E1C and L1C/A were determined using E5a and L2C(L) signals, respectively, as observations \(L_{2}\), and where this was not possible, the L2W signal was used. For the remaining observations, Equation (10) was used, using E1C and L1C/A observations as \(L_{1}\). The CMC series determined in this way were filtered using \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**System**} & \multirow{2}{*}{**Signal**} & **Number of** & \multirow{2}{*}{**System**} & **Signal** & **Number of** \\  & & **Satellites** & & **Satellites** \\ \hline \multirow{4}{*}{**Galileo**} & E1-C & 19 & & L1-C/A & 32 \\ \cline{2-5}  & E5a-Q & 19 & & L2C(L) & 20 \\ \cline{1-1} \cline{2-5}  & E5b-Q & 19 & & L2W(P(Y)) & 32 \\ \cline{1-1} \cline{2-5}  & E5-Q & 19 & & L5 Q & 12 \\ \cline{1-1} \cline{2-5}  & E6-C & 19 & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Type of observations used in the experiment. Figure 1: Environment at the WUT antennas site (in the foreground is WUT2 station). a moving average, for \(k=1000\). The moving average acts as a low-pass filter. Such a value of the \(k\) parameter, which at an observation interval of 1 s gives a period of approximately 35 min, allows for the elimination of not only the impact of ambiguity but also hardware biases [24]. The determined values of the STD of the multipath impact on code observations (see Equation (19)), depending on the satellite elevation are presented in Figure 2. The statistics were calculated for 10-degree elevation bins, starting from an elevation mask of 10\({}^{o}\). The obtained results concern observations recorded by the WUT2 station. The STD of the multipath effect are very close to each other, with two apparent exceptions. The smallest values, for all elevation bins, were obtained for the E5 AltBOC observation. The highest error values, in turn, were obtained for the L2W observation, which may be influenced by the specificity of tracking this observation, related to SNR degradation and its impact on the observation tracking accuracy. For other types of observations, for the lowest elevation bin, the multipath impact on Galileo turns out to be only marginally smaller than that for GPS. It is likely that, if the observations were recorded in an environment more susceptible to the multipath effect, much larger differences for the different signal types would be visible. The graph shows the general correlation between the magnitude of the multipath and the satellite elevation. Figure 3 shows the STD of measurement noise, determined on the basis of Equation (18). In this case, much larger discrepancies between given observations are visible.