## 5 Discussion and Conclusions  
In this study, the positioning performance of GRAPHIC and uncombined SF-PPP models was evaluated and compared. We firstly evaluated these two approaches using one-week datasets from 40 MGEX stations in case of any observational quality issues. The two approaches achieved very similar positioning accuracy, with 0.1 m and 0.2 m in the horizontal and vertical directions, respectively. However, the uncombined approach manifested faster convergence than GRAPHIC by 40.7%, 20.0%, and 13.8% in the east, north, and up components, respectively, owing to the adoption of high-precision carrier phase observations as well as ionospheric parameterization.  
We collected smartphone-based datasets using the Huawei P40 smartphone equipped with an external geodetic-grade antenna (P40-EXT) as well as its internal antenna (P40-INT) for comparison and analysis. Firstly, the raw observations from these two smart devices were compared in terms of the C/N0 value and measurement noise. The code measurement noise with the internal antenna case were 0.27 m larger than the external, while little differences were found for carrier phase observations. In addition, the P40-INT pseudorange noise showed strong correlations with respect to the C/N0 values. The P40 observations from the GPS L1, BDS BII, and Galileo E1 frequencies were utilized to conduct SF-PPP. The errors of uncombined SF-PPP of the external antenna case were 0.14 m, 0.15 m, and 0.33 m in the east, north, and up components, respectively, showing an improvement of about 31% in the up direction when compared with the GRAPHIC solution. The C/N0-dependent weighting model performed much better than the elevation-dependent model for the internal antenna case with an improvement of about 30-60%, especially in the vertical component. It improved the GRAPHIC positioning accuracy to 0.65 m, 0.42 m, and 0.90 m in the east, north, and up directions, respectively, and for the uncombined approach, the precision could even reach 0.72 m, 0.51 m, and 0.66 m in the east, north, and up directions, respectively.  
Figure 11: Statistical values of positioning errors for different smartphone devices of the SF-PPP result series at the end of 120 min.  
**Author Contributions:** Conceptualization, M.L. and W.L.; Data curation, Q.Z.; Formal analysis, K.J.; Funding acquisition, M.L. and Q.Z.; Investigation, Z.L., W.L. and K.J.; Methodology, M.L. and W.L.; Project administration, M.L., W.L. and Q.Z.; Resources, Q.Z.; Software, Z.L., T.H. and J.Z.; Supervision, M.L.; Validation, J.Z.; Visualization, Z.L.; Writing--original draft, Z.L.; Writing--review and editing, W.L. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was sponsored by the National Natural Science Foundation (grant no. 42004020, 42074032, 41931075, and 42030109), the China Postdoctoral Science Foundation (grant no. 2021M692460), the Fundamental Research Funds for the Central Universities (grant no. 2042021k0060, 2042021k0063), and the Wuhan Science and Technology Bureau (grant no. 2019010701011391).  
**Institutional Review Board Statement:** Not applicable.  
**Infrared Consent Statement:** Not applicable.  
**Data Availability Statement:** All data included in this research are available upon reasonable request by contacting with the corresponding author.  
**Acknowledgments:** We would like to acknowledge IGS for providing the ground GNSS tracking datasets and precise GNSS orbit and clock products.  
**Conflicts of Interest:** The authors declare no conflict of interest.