# Real-Time Phase Bias Estimation for BeiDou Satellites Based on Consideration of Orbit Errors
## 6 Conclusions and Outlook  
With its five GEO, five IGSO and four MEO satellites, the BDS system plays an important role in PPP in the Asia-Pacific region. However, because of the lack of sufficiently well-distributed tracking stations and a poorly developed solar radiation pressure model, the orbit precision of the BDS satellites is low when compared with that of the GPS satellites [24; 25; 27]; this is particularly true for the GEO satellites, which remain nearly stationary relative to the ground tracking stations. This poor orbit precision will affect the NL FCB estimation results of BDS satellites quite severely. This paper proposes a strategy for estimation of the GPS + BDS FCB based on consideration of the orbit error, and has demonstrated a GPS + BDS FCB estimation approach along with PPP ambiguity resolution in a simulated real-time model using the stations distributed across China.  
In general, more than 98% of the a posteriori residuals of the WL ambiguities are within \(\pm\)0.25 cycles for the GPS, IGSO, and MEO satellites; while this figure falls to 87% for the GEO satellites. After the orbit errors were taken into consideration, more than 94% of the NL a posteriori residuals were within \(\pm\)0.1 cycles for all satellite types. The contribution of the BDS observations to GPS-only PPP-IAR has also been investigated. In kinematic PPP, within a 5-min period, the fixing percentage for the solo GPS solution was only 4.27%; however, when the BDS was added, the percentage improved significantly to 64.56%. For observation periods of 10 min and 20 min, the fixing percentages were 18.33% and 46.25%, respectively, for the solo GPS, but rose to 81.53% and 91.73%, respectively, when using the GPS + BDS solution. With obvious contrast, if the GPS + BDS mode is used without consideration of the orbit errors, the fixing percentage only reaches 1.78% for a time period of 6 min and reaches 4.77% for both 10-min and 20-min observation periods. After the ambiguities are correctly fixed, the RMS position accuracy is degraded to 0.77, 0.67, and 2.88 cm for the north, east, and up directions, respectively, with improvements of 9.4%, 2.9%, and 2.0% when compared with the GPS-only solution.  
Based on the scale factor, a wider tracking network distribution enables better orbit error estimation. The network used in this study covers an area with a radius of 1500 km, which is relatively small when compared with the globally distributed network of tracking stations. Therefore, with this network, we can only solve \"part\" of the orbit error, which may only satisfy the requirements for PPP-IAR within this network. Using greater numbers of Multi-GNSS Experiment (MGEX) stations [43], we intend to investigate the performance of the proposed method over larger networks. In addition, the higher-order ionospheric delays and the bending effect both affect the PPP solutions [44]. In this study, we have not considered the higher-order ionospheric delays as part of our PPP processing. Therefore, in future work, we will also consider these higher-order ionospheric delays and analyze their contributions to PPP-IAR performance.  
[PERSON] conceptualized the initial idea and experimental design. [PERSON] performed the experiments. [PERSON] wrote the main manuscript text. [PERSON] helped with data collection and analysis of the results.  
This work was partially supported by the National Natural Science Foundation of China (No. 41704033), the Shenzhen Future Industry Development Funding Program (No. 201607281039561400), the Shenzhen Scientific Research and Development Funding Program (No. JCYJ20170818092931604), and the Research Program of Shenzhen S&T Innovation Committee (No. JCYJ20170412105839839).  
The authors declare no conflict of interest.