# A Novel Method to Mitigate the Multipath Error for BDS-2 Dam Deformation Monitoring
## 3 Results
### Data Collection and Processing  
In order to assess the performance of the MHGM, BDS-2 data collected as a part of the deformation monitoring of reservoir were processed. The SF method was used as a comparison to prove the advantage of MHGM. As shown in Figure 2, four BDS-2 stations were built on the dam and all the stations were capable of capturing BDS signal with 1 Hz sampling rate. The date spans a period of time from DOY 44 to 55 of the year 2019. The satellite orbital repeat times for BDS-2 satellites were computed using Keplerian orbital elements from broadcast ephemerides. Generally, the orbital repeat times are 86155 s (23 h 55 min 55 s) for BDS-2 GEO/IGSO and six days plus 84697 s (23 h 31 min 37 s) for BDS-2  
Figure 1: Distribution of hemispherical grid points.  
MEO. Details of the models and strategies related to data processing of PANDA software are shown in Table 1.  
The model parameters were set as follows: \(B_{0}=5^{\circ}\), \(B_{1}=85^{\circ}\), \(d_{b}=2^{\circ}\) and \(d_{l}=2^{\circ}\). In order to improve the reliability of the MHGM results, three equations are involved in the  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **Model** & **Constraint** \\ \hline Observation & BDS-2 B1 & 0.02 cycle, 1.0 m \\ Observation weight & Satellite elevation & / \\ Cutoff elevation & 7 degree & / \\ Phase center pattern & igs14.atx & / \\ Tropospheric delay & Saastamoinen + GMF & priori covariance \\ Satellite clock & Broadcast & / \\ Receiver clock & Range estimating & priori covariance 9000 m \\ EOP & Fixed to IERS & / \\ \hline \hline \end{tabular}
\end{table}
Table 1: Model and parameters for data processing.  
Figure 2: Distribution of BDS-2 stations used for reservoir deformation monitoring, where the C0100 station is the base station and the other stations are monitoring stations (the origin of the background image is Google Earth).  
solution. In addition, correlation constraints were added between grid point parameters, and the absolute value of grid point parameters was less than 1/4 wavelength [3]. In order to reduce the coarse value and improve the stability of grid point results, the additional correlation constraint between the grid point parameters was imposed. It was found that setting the value from 5 mm/degree to 5 cm/degree has little effect on the final model result, so the empirical variation value was set to 1.0 cm/degree.  
For both MHGM and SF methods, the same fixed DD ambiguities were used to establish the multipath model. The DD residuals before the day of interest were shifted according to the orbital repeat time and then stacked for each pair. These stacked residuals were low-pass filtered with a cutoff of 10 s to generate multipath corrections. Finally, the phase observations on the day of interest were corrected, and then processed for kinematic relative positioning in simulated real time. The strategies of the solution adopted in this study are as shown in Table 2. For example, if the date of the test data is DOY 51, the modeling data of GEO/IGSO and MEO for the SF method are DOY 50 and 44, respectively. The modeling data of GEO/IGSO and MEO for the MHGM method were from DOY 44 to 50, which is a total of seven days and so on for other test data days.