# GNSS Real-Time Precise Point Positioning in Arctic Northeast Passage
## 5 Conclusions  
GNSS is one of the most widely used positioning methods in the Arctic regions. The main algorithm used in the polar regions is GNSS single-point positioning (SPP); however, its meter-level positioning accuracy is poor. Furthermore, its precision cannot meet the requirements of some Arctic projects, e.g., precise oil drilling. Precise point positioning (PPP) can achieve sub-decimeter and centimeter-level positioning accuracy using one GNSS receiver. Some scholars have researched PPP algorithms in the polar regions; however, it still cannot meet the requirements of real-time positioning due to the several-day latency of the precise ephemeris. Few scholars have studied RT-PPP because of its lack of reliable communication links. Nevertheless, real-time services provided by IGS and easy-access satellite communication systems available in the NEP have opened the opportunity for precise multi-GNSS products in real-time. Therefore, in our paper, we analyzed the use of RT-PPP in the Arctic NEP. We evaluated the positioning performance of RT-PPP in the NEP during the period between 10 September and 20 September 2019. Moreover, we collected our GNSS data using a U-blox F9P receiver installed on the M/V TIANHUI. We also evaluated the satellite signal quality. Our results show that the maximum satellite evaluations vary considerably with latitude for GPS and Galileo, while BDS is less sensitive to latitude changes due to the contribution of BDS IGSO. PDOP is usually inversely proportional to NSAT, reflecting the quality of the satellite structure. We found that the NSAT for GPS and Galileo is larger than that of BDS; as a result, PDOP for GPS and Galileo is lower and more stable. Moreover, the above three systems have a total of 24 satellites that yield the smallest PDOP values. We also observed consistent daily SNR values prone to environmental changes. On the other hand, multipath errors showed large variations over different bands, as well as environmental changes, where the differences sometimes reached the decimeter level. In addition to the satellite signal quality, the real-time SSR corrections also affected the positioning performance. We used CLK93 products, which include multi-GNSS correction information, and investigated their performance over an 11-day testing period. Our results show that Galileo has the best performance, both in satellite orbit and clock, which are approximately 0.056 m in 3D and 0.084 ns, respectively. GPS shows comparable performance to Galileo, with 0.063 m in the 3D component and 0.130 ns for the real-time clock. BDS and GLONASS show some disadvantages, with BDS exhibiting the lowest orbit accuracy of 0.142 m, while GLONASS yielded the worst satellite clock of 0.623 ns. As for the RT-PPP performance in the NEP, 1-meter-level positioning accuracy can be achieved with GIM-based SF RT-PPP, while the DF RT-PPP model reaches a sub-decimeter and centimeter-level accuracy. With a multi-GNSS combination, we can further improve the precision of the RT-PPP for both SF and DF models. Furthermore, with multi-GNSS, the average RMS value in the horizontal(vertical) direction is 0.080(0.057) m, a 70% improvement over single-GPS solutions. However, due to the complexity of the marine environment, fault observation data may appear. Therefore, we will carry out more effective fault detection in our future research to further improve the reliability of RT-PPP in the Arctic region [31; 32]. \begin{table}
\begin{tabular}{l c c c c c} \hline \hline  & **E (m)** & **N (m)** & **2D (m)** & **U (m)** & **3D (m)** \\ \hline Klobuchar & 1.925 & 3.917 & 4.365 & 2.630 & 5.096 \\ GIM & 1.056 & 0.978 & 1.440 & 0.863 & 1.679 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: RMS values of Klobuchar–based and GIM–based SF RT–PPP solutions in the east, north, horizontal, up, and 3D directions from 10:00 to 22:00 on 12 September 2019. **Author Contributions:** Conceptualization, methodology, software, and writing--original draft preparation, M.D.