Modeling and assessment of real-time precise point positioning timing with multi-GNSS observations

Real-time precise point positioning (PPP) method is of great interest for global navigation satellite systems (GNSS) time application with multi-GNSS observations. In this study, a multi-GNSS precise timing approach using Centre National d'Etudes Spatiales (CNES) real-time products was presented to improve the reliable of precise timing. Users can obtain the difference between the local time (time of rover receiver) and UTC(k) directly using a GNSS receiver, once the CNES products are aligned to UTC(k) by a multi-GNSS PPP approach. In other words, the reference times of the realigned products for GPS, GLONASS, BDS-2 and Galileo are UTC (k). Then, users can obtain the difference between the local time and UTC(k) directly using any single-system or multi-GNSS combination. Note that the receiver hardware delay needs to be calibrated before timing application. Numerical analyses clarify how the multi-GNSS precise timing approach performs. First, the standard deviation (STD) of the difference between the multi-GNSS timing results and the clock difference from the IGS final products is shown to be less than 0.5 ns. The multi-GNSS solutions outperform that of a single system. Furthermore, GPS-only PPP timing solutions perform better than that of GLONASS and Galileo-only. In addition, the maximum reductions of STD values are up to 33.6%, 11.6%, 14.6%, 25.6% for GPS-only, GLONASS-only, Galileo-only and multi-GNSS timing, respectively, using a receiver clock model. Second, the frequency stability of the multi-GNSS scheme is slightly better than GPS-only. For single-system PPP timing, GLONASS-only performs worst, while GPS-only performs best. The maximum improvements of frequency stability are up to 61.9%, 67.1%, 90.6%, 65.8% for GPS-only, GLONASS-only, Galileo-only and multi-GNSS timing, respectively, with a receiver clock model using the realigned products. More interestingly, we found that the performance Galileo-only was improved with the observations on 2019 as compared to Galileo with the observations on 2018.