Performance Assessment of Positioning Based on Multi-Frequency Multi-GNSS Observations: Signal Quality, PPP and Baseline Solution

With the advances and modernization of GPS, GLONASS, BDS, Galileo and QZSS, multi-frequency and multi-system joint positioning has become the mainstream positioning and navigation. Therefore, it is of great importance to perform a comprehensive assessment of the signal quality and positioning performance of multi-frequency and multi-GNSS. In this work, we used the multi-GNSS observation data collected by the Multi-GNSS Experiment (MGEX) of the International GNSS Service (IGS), Hong Kong CORS, and GNSS Research Centre of Curtin University. Firstly, the quality of multi-frequency and multi-GNSS observation data is evaluated and analyzed. Then, the five-system triple-frequency ionospheric-free combined PPP (IF-PPP) and uncombined PPP (UC-PPP) models are established, and their performance in static PPP and kinematic PPP is evaluated. Finally, the performance of multi-frequency multi-GNSS in short baseline, medium long baseline and very long baseline is evaluated. Based on the results, three major observations are made as follows. (1) The signal-to-noise ratios (SNRs) of the five constellations (i.e. BDS, GPS, GLONASS, Galileo and QZSS) are all above 30dB Hz and the multipath errors are within 1m, indicating good signal quality. (2) For static PPP, compared with IF-PPP model, the convergence time of triple-frequency UC-PPP model is reduced by 4.9%, 3.2%, and 13.8% for BDS-2+3, GPS, and GPS/GLONASS/BDS-2+3/Galileo/QZSS, respectively. However, the positioning accuracy of triple-frequency UC-PPP model is improved by 15.9%, 11.8%, and 10.9%, respectively, compared with IF-PPP model. For kinematic PPP, with the increased number of BDS-3 satellites, BDS has achieved better positioning results than GPS. (3) In terms of baseline solution performance, the accuracy of triple-frequency GPS/GLONASS/BDS/Galileo/QZSS combined baseline solution is about 60% higher than that of triple-frequency GPS-only baseline solution, showing a significant performance gain due to the use of multi-GNSS observations.