## 3 Results and Discussion
### Satellite Clock Comparison  
The real-time DD clock time series with dual-frequency and multi-frequency signals are depicted in Figures 3 and 4, respectively. Apart from the convergence part on the first day, the DD clocks show an apparent DBD phenomenon. Two potential reasons may contribute to the clock DBD. First, the reference clocks, which are generated on a daily basis, will experience jumps at day boundaries and then impact the resulting DD clocks. Second, the real-time clocks are estimated with orbit fixed to GFZ post-processed product. The GFZ daily orbit is determined with independent 24-h observation data, and therefore will inevitably be affected by the DBD phenomena. The orbit DBD will affect the orbit interpolation around day boundaries and then have an impact on the corresponding real-time clocks. \begin{table}
\begin{tabular}{c c} \hline \hline
**Items** & **Models** \\ \hline Basic observables & Raw code and phase; cut-off elevation: 10.0 deg; sampling rate: 30.0 s \\ \hline Weighting strategy & Code: 0.3 m; phase: 0.3 cm; the sigma increases with decreasing elevation angle using the function 1/sin(elevation) \\ \hline Antenna phase center & IF/UC model for clock estimation: corrected with PCO and PCV values from igs14.atb file, GPS values adopted for BDS-3 at the receiver end; \\ GFIF model for IFCB estimation: corrected with PCO and PCV values from either igs14.atv or igsR3.atv file \\ \hline Attitude model & Modeled [19] \\ \hline Tropospheric delay & Hydrostatic part according to the formula of [20] as given by [21] \\  & with surface pressure computed with GPT2w model [22]; Wet part estimated as random walk process with VMF1 (Vienna Mapping \\  & Function 1) [23]; Horizontal gradient model not considered \\ \hline Ionospheric delay & 1 st order eliminated for IF/GFIF model and estimated for UC model, higher-order not considered \\ \hline Tidal displacements & Solid Earth tides, ocean loading and pole tides according to IERS \\  & Conventions 2010 [24] with FES2004 ocean tide model [25] \\ \hline Phase wind-up effect & Corrected [26] \\ \hline Receiver clock & Estimated as white noise process \\ \hline Satellite clock & Estimated as white noise process \\ \hline Phase ambiguities & Estimated as constant each observation pass \\ \hline Satellite orbit & Fixed to the post-processed solution from IGS ACs \\ \hline Earth orientation parameters & Fixed to IERS (International Earth Rotation Service) Bulletin A \\ \hline Estimator & Extended Kalman filter \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Processing strategy for real-time BDS-3 clock and IFCB estimation. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameters** & **Initial State** & **Initial Variance** & **Process Noise** \\ \hline Satellite clock & Post-processed solution & \(1\times 10^{4}\) m\({}^{2}\) & - \\ Receiver clock & SPP & \(1\times 10^{4}\) m\({}^{2}\) & - \\ Station zenith wet delay & 0.0 m & \(0.25\) m\({}^{2}\) & \(3\times 10^{-8}\times 30\) m\({}^{2}\) \\ Ambiguity & Aligned to code & \(1\times 10^{8}\) m\({}^{2}\) & \(0.0\) m\({}^{2}\) \\ Satellite IFCB & 0.0 m & \(1\times 10^{4}\) m\({}^{2}\) & - \\ Receiver IFCB & 0.0 m & \(1\times 10^{4}\) m\({}^{2}\) & - \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Filter setting for real-time BDS-3 clock and IFCB estimation. Figure 4: Real-time satellite clock with multi-frequency signals, the top one denotes UC model with B1I/B3I/B1C signals, the middle one denotes UC model with B1I/B3I/B2a signals, the bottom one denotes UC model with B1I/B3I/B1C/B2a signals. Figure 3: Real-time satellite clock with dual-frequency signals, the top one denotes IF model with B1I/B3I signals, the middle one denotes UC model with B1I/B3I signals, the bottom one denotes UC model with B1C/B2a signals. The real-time clock solutions are similar for all of the six models with the exception of the B1C/B2a UC model.