## 3 Results and Discussion
These numbers are just used to clarify the condition of the inputs for the SICB modeling. The number of epoch-wise MP values of BDS-2 MEO satellites is significantly smaller than that of BDS-2 IGSO satellites due to the relatively shorter tracking time. Theoretically, the accuracy of the model parameters will be improved when more datasets are involved in the SICB modeling. However, no more improvements can be achieved after the amount of data reaches a critical point, even if more datasets are subsequently included [23]. According to [PERSON] et al. [23], the number of epoch-wise MP values is sufficient for the SICB modeling in this study. Figure 8.0 SICB correction model as a function of elevations on B1 and B3 frequencies for each BDS-3S MEO and IGSO satellite. Figure 8.1 Distribution of uncorrected and corrected MP combination time series for BDS-2 IGSO satellites. Figure 8.2 Distribution of uncorrected and corrected MP combination time series for BDS-2 MEO satellites. To further analyze the improved measurements, we reconstruct the elevation-dependent SICB correction model for the BDS-2 IGSO and MEO satellites using the code observations corrected by the previously established SICB correction model. The results are shown in Figure 8.3 It is clearly seen that the elevation-dependent model values after applying the SICB corrections are close to zero, indicating the successful correction of SICB for the code observations. The improved code measurements can be safely used for precise applications. As shown in the Introduction section, many researchers have established various SICB correction models [5; 8; 9; 10; 11]. These existing models are all referred to as \"traditional SICB correction models\" in this paper. However, we cannot compare our improved SICB correction model with these traditional models one by one, because the datasets used for SICB modeling are different. For comparison, the traditional SICB correction model is also established by ourselves based on a comprehensive consideration of the advantages claimed for these traditional models [5; 8; 9; 10; 11]. The modeling strategies of the traditional SICB correction model can be summarized as: the lumped term of integer phase ambiguities and constant hardware delays is determined based on the average values of MP series obtained with original code observations over each continuous tracking arc; the elevation node separation is set to \(5^{\circ}\); the model parameters are estimated by the least-squares adjustment for each satellite. Table 1 summarizes the major characteristics of the traditional and improved SICB correction models to exhibit the differences between their modeling strategies. The estimated model parameters of the traditional SICB correction model for BDS-2 IGSO and MEO satellites are provided in Figure 8.4 Compared with the modeling results shown in Figure 10, the traditional and improved SICB correction models have similar trends against elevations. However, the traditional SICB corrections miss a lot of detail about elevation-dependent variations, and fluctuate much more than the improved SICB corrections. In addition, the absolute level of SICB corrections also shows differences for the traditional and improved models. For example, the improved SICB corrections on the B3 frequency close to the zenith are approximately 0.3 m for C07, while the corresponding traditional SICB corrections are approximately 0.22 m.  
Figure 8.5 Reconstructed SICB correction model as a function of elevations on B1, B2 and B3 frequencies for each BDS-2 MEO and IGSO satellite using the code observations corrected by the previously established SICB correction model.