## 4 Results and Discussion
### Performance of the Presented Smartphone Dynamic PPP  
In this section, the results of the presented smartphone PPP based on the BDS PPP-B2b products and IGS real-time products in the dynamic test are presented. The reference results for this dynamic experiment are calculated by the tight RTK/INS integration. The dynamic smartphone's GPS+BDS data are processed by (1) GPS-only PPP using the BDS PPP-B2b products based on the hybrid weight function and the mixed-frequency measurements for L1 and L5 (GPS-PPP-b2b-MF-Com); (2) GPS+BDS-3 PPP using the BDS PPP-B2b products based on the elevation-dependent weight function and measurements for L1 and B1 (GB-PPP-b2b-SF-Ele); (3) GPS+BDS-3 PPP using the BDS PPP-B2b products based on the C/N0-dependent weight function and measurements for L1 and B1 (GB-PPP-b2b-SF-CN0); (4) GPS+BDS-3 PPP using the BDS PPP-B2b products based on the hybrid weight function and measurements for L1 and B1 (GB-PPP-b2b-SF-Com); (5) GPS+BDS-3 PPP using the BDS PPP-B2b products based on the hybrid weight function and the mixed-frequency measurements for L1, L5, and B1 (GB-PPP-b2b-MF-Com); (6) GPS+BDS PPP using the ultra-rapid precise products provided by IGS based on the hybrid weight function and the mixed-frequency measurements for L1, L5, and B1 (GB-PPP-ULT-MF-Com); and (7) GPS+BDS PPP using the final precise products provided by IGS based on the hybrid weight function and the mixed-frequency measurements for L1, L5, and B1 (GB-PPP-FIN-MF-Com), respectively.  
Figure 11 provides the positioning errors of the dynamic PPP of the MI8 smartphone by using different orbit/clock products, and the corresponding RMS values are listed in Table 5. As presented, the 3D positioning accuracy based on the BDS PPP-B2b products performs obviously worse than those based on the ultra-rapid precise products and the final products, especially while using the GPS+BDS-3 single-frequency observations based on the elevation-dependent stochastic weight model. However, such a positioning accuracy loss is mainly in the vertical direction. While evaluating the positioning accuracy in the horizontal component, these BDS PPP-B2b product-based smartphone PPP schemes can provide almost the same positioning accuracy as the IGS product-based PPP schemes, except for the GB-PPP-b2b-SF-Ele scheme. This may be because the elevation-dependent weight function cannot indicate the real quality of smartphones' GNSS observations.  
Figure 11: Positioning errors of dynamic PPP using different products based on different weight functions.  
Specifically, compared to the results of the GPS-PPP-b2b-MF-Com scheme, the positioning accuracy of the GB-PPP-b2b-MF-Com scheme is improved from 0.68 m, 0.65 m, and 3.58 m to 0.61 m, 0.55 m, and 3.16 m, with the corresponding improvements of 10.29%, 15.38%, and 11.73% in the east, north, and vertical components, respectively. Compared to the results of the GB-PPP-b2b-SF-C/N0 scheme, the GB-PPP-b2b-SF-Com scheme provides 10.26%, 15.31%, and 14.99% positioning accuracy improvements in the three components, and such improvement percentages are 74.64%, 72.88%, and 36.85% when compared with the results of the GB-PPP-b2b-SF-Ele scheme. In general, the positioning accuracy of the GB-PPP-b2b-MF-Com scheme is higher than that of the GB-PPP-b2b-SF-Com scheme (0.70 m, 0.83 m, and 3.29 m), with the accuracy upgradation of 12.86%, 33.73%, and 3.95% in the east, north, and vertical directions, respectively. Moreover, compared to the positioning accuracy of the GB-PPP-FIN-MF-Com scheme (0.60 m, 0.79 m, and 0.81 m), about 8.33%, 11.39%, and 40.74% positioning accuracy degradations occur in the GB-PPP-ULT-MF-Com scheme, and about 1.67% and \(-\)30.38% positioning accuracy impacts in the GB-PPP-b2b-MF-Com. The positioning accuracy of the GB-PPP-b2b-MF-Com scheme is about three times higher than that of the GB-PPP-FIN-MF-Com scheme in the vertical component. In general, the positioning accuracy of the smartphone PPP model provided in this work can almost reach the same positioning accuracy as that presented in [28].