# BeiDou Geostationary Satellite Code Bias Modeling Using Fengyun-3C Onboard Measurements
## 3 Results
### Satellite- and Receiver-Induced Code Biases and Modeling
However, a different behavior did exist in C05 B1 relative to others, and its amplitude was much larger than that of the C01 to C04 group. Comparing different groups, the 2 lines of GEO and IGSO B2 almost overlap together, so they should be placed in the same category. It is also interesting that when the elevation angle was below \(60^{\circ}\), the difference between groups in the same frequency was less than 5 cm, except for the C01 to C04 B1 group. Table 2 and Figure 11 show the comparison with [PERSON] and [PERSON]'s model values. There is a good fit between the lines even if the elevation angle falls below \(40^{\circ}\). The RMS of the differences is less than 10 cm. Specifically, the differences for IGSO at zero elevation seem relatively larger. This can be attributed to the contamination of the relative larger noise at low elevation. Also, [PERSON] and [PERSON]'s MEO model values are slightly smaller than those of the derived model, which results in a grid of MEO with relatively larger values after application of [PERSON] and [PERSON]'s MEO model in Figure 9. This also explains the remaining trend components in IGSO-MEO panels. But these differences seem only marginal when considering the magnitude of the systematic variations. To verify the correctness of the derived models for the BDS-satellite-induced biases and the static GNOS-receiver-induced biases, some examples of MP combinations are shown. The same satellite arcs are used as those in Figure 4. Figures 12 and 13 show that the MP time series regained the symmetry in elevation after application of the receiver-induced bias corrections for each of the 2 BDS frequencies. However, if only the satellite-induced bias corrections was used, the remaining receiver-induced biases was very evident in the MP variations, as shown in the Figures. When both model corrections were applied, these systematic biases disappeared. Regardless of the effect of the periodic signal mentioned above, the MP time series already shows the typical elevation-dependent variations, which are smallest for high elevations and largest for the ascending or descending satellites. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Linear Model Node Values (m)**} \\ \cline{2-7}
**Elevation (\({}^{\circ}\))** & \multicolumn{2}{c}{**GEO**} & \multicolumn{2}{c}{**IGSO**} & \multicolumn{2}{c}{**MEO**} \\ \cline{2-7}  & **B1 (C01–C04)** & **B1 (C05)** & **B2** & **B1** & **B2** & **B1** & **B2** \\ \hline
0 & \(-\)0.14 & \(-\)0.43 & \(-\)0.46 & \(-\)0.38 & \(-\)0.45 & \(-\)0.42 & \(-\)0.41 \\
10 & \(-\)0.25 & \(-\)0.37 & \(-\)0.27 & \(-\)0.35 & \(-\)0.30 & \(-\)0.37 & \(-\)0.30 \\
20 & \(-\)0.27 & \(-\)0.31 & \(-\)0.26 & \(-\)0.34 & \(-\)0.31 & \(-\)0.35 & \(-\)0.34 \\
30 & \(-\)0.18 & \(-\)0.17 & \(-\)0.14 & \(-\)0.22 & \(-\)0.17 & \(-\)0.24 & \(-\)0.20 \\
40 & \(-\)0.09 & \(-\)0.14 & \(-\)0.09 & \(-\)0.12 & \(-\)0.10 & \(-\)0.17 & \(-\)0.14 \\
50 & \(-\)0.05 & \(-\)0.01 & \(0.01\) & \(-\)0.01 & \(0.00\) & \(-\)0.03 & \(-\)0.00 \\
60 & 0.03 & 0.17 & 0.12 & 0.13 & 0.11 & 0.19 & 0.16 \\
70 & 0.12 & 0.32 & 0.20 & 0.24 & 0.21 & 0.56 & 0.39 \\
80 & 0.12 & 0.45 & 0.25 & 0.28 & 0.27 & 0.94 & 0.56 \\
90 & 0.22 & 0.69 & 0.31 & 0.36 & 0.35 & 1.02 & 0.63 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Seven groups of the final derived elevation-dependent correction node values for BDS-satellite-induced biases.