## 5 Discussion  
The simulation experiments carried out in this study comprehensively evaluate the proposed tightly coupled GNSS/INS navigation system, focusing on the accuracy, robustness, and computational efficiency of the system. Our results demonstrate several key findings.  
Firstly, the proposed combined navigation scheme shows a significant improvement in state estimation accuracy compared to the LC navigation system. Even in environments with poor satellite observation conditions, the TC system provides a reliable attitude estimation. This robustness is attributed to the multi-source data fusion, which includes the pseudo-range, pseudo-range rate, and dual-antenna observation from the GNSS and the horizontal attitude angle from the VG. The VG algorithm is particularly effective in correcting horizontal attitude errors during periods of GNSS signal degradation, thereby enhancing the overall stability of the navigation solution. Secondly, the weighted quasi-optimal satellite selection algorithm proposed in this paper effectively reduces the computational burden of the navigation system without compromising the accuracy of the observation  
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **Mean Psr-Std** & **Mean Nav-Err** \\ \hline WQOSA & 1.787 & 3.241 \\ QQSA & 2.237 & 3.941 \\ \hline \hline \end{tabular}
\end{table}
Table 6: The average curves of psr-std and nav-err in the mentioned time period for the WQOSA and QQSA.  
Figure 12: Every satellite selected in the WQOSA and QQSA has a standard deviation of the pseudo-range error (psr-std). (**a**) By taking the average of all psr-std values, we plot the mean values of psr-std over the experimental time period in the chart. (**b**) Additionally, we also plot the mean curve of the navigation error standard deviation (nav-err) for the corresponding time intervals.  
data. By selectively screening observable satellites, the algorithm maintains high computational efficiency, which is crucial for real-time navigation applications. The comparison experiments with the OSA and QOSA highlight the advantages of our method in terms of both computational efficiency and engineering practicability.  
The performance of the TC system under non-line-of-sight (NLOS) conditions and multipath effects also warrants discussion. Although the TC scheme maintains navigation functionality in such environments, errors introduced by NLOS reception and multipath can still be significant. Future work could explore the incorporation of advanced multipath mitigation techniques or the integration of additional complementary sensors to further enhance system performance.  
In terms of practical applications, the reduced computational load and improved accuracy make the proposed system highly suitable for smart driving vehicles and other civilian carriers where cost and real-time performance are critical factors. The integration of the VG algorithm and the weighted quasi-optimal satellite selection algorithm presents a balanced approach that addresses both the accuracy and efficiency requirements of modern navigation systems.  
In conclusion, the proposed tightly coupled GNSS/INS navigation system with multi-source data fusion and an optimized satellite selection algorithm demonstrates significant improvements in navigation accuracy, robustness, and computational efficiency. These results support the feasibility of deploying such systems in real-world applications where high precision and reliability are essential.