## 4 Discussion  
With a noticeable enhancement in orbit accuracy observed upon integrating ISL observations into data processing, we conducted a comparative analysis of various modeling strategies for the BDS-3's cuboid satellite body. Previous research indicates that the introduction of ISL data significantly reduces the correlation between ECOM model parameters [26]. However, within the context of the ABW model, while the ISL decreases the correlation among orbit parameters, it also tends to slightly increase the correlation between the optical parameters of the +X/\(\pm\)Z panels to some extent. This may be attributed to the parameter settings of the model. The optical parameters of the satellite buses in the ABW model are correlated, whereas the parameters of ECOM are inherently orthogonal, allowing the ISL to reduce the ECOM parameter correlation by enhancing the geometry observation.  
The biases of SLR residuals for the CAST-A satellite based on G1 and J1 are comparable during modeling. The contribution of ISLs is to reduce the dispersion of the SLR residuals. This is well matched with the improved SLR residuals of ECOM+G1/J1 shown in Figure 9. Notably, although ECOM outperforms ECOM+G1/J1 in DBD, the OADEV of the clock offsets demonstrates the superiority of ECOM+J1 over other strategies. For the SECM-A satellites, the a priori model established using J1 can reduce the systematic SLR biases introduced by the G1 model by 1.7 cm. Based on the improvements in DBD and the averaged OADEV values, we found that the use of ISL enhances SECM satellite modeling more effectively than CAST satellites. This is consistent with the understanding that the area differences between SECM satellite X/Z panels results in a more rectangular body shape. However, systematic biases in the SLR residuals persist for both CAST and SECM satellites when using the a priori model compared to the orbits derived from SRP modeling. It is plausible that additional unidentified errors remain uncorrected in the a priori model.  
For the CAST satellites carrying SAR antennas, we considered the impact of their self-shadowing. The increased illuminated \(\pm\)Z area resulting from the SAR antenna was factored in \(\beta\) angles. We found that considering the SAR antenna only slightly improved the DBD accuracy and the OADEV. However, the OADEV series shows a systematic trend with respect to the \(\beta\) angle. This systematic trend was significantly reduced with the a priori model constructed with the introduction of ISL data. With regard to the SECM-B satellites C43 and C44, this study modeled them as separate types of SECM satellites due to the unavailable satellite body structure information. Despite the limited number of orbit arcs within the modeling timeframe, the use of ISLs enhances DBD and OADEV by about  
Figure 11: OADEV at 9000 s of CAST-B (C33) satellite with respect to the \(\beta\) angle.  
2.2% and 6.7% on the base of the a priori model established by G1. This study suggests that the magnitude of the effects of SAR panels is small, and it can be absorbed with ABW parameters without requiring separate consideration. Additionally, the accuracy of the a priori model may be enhanced if more accurate SAR antenna parameters of CAST-B and SECM-B satellites are released by the official agency.