Ionospheric delay is one of the most problematic errors in satellite-based positioning data processing. The Global Ionospheric Map (GIM), which is publicly available daily in various analysis centers, is thus vitally important for positioning users. There are variations in the accuracy and consistency of GIMs issued by Ionosphere Associate Analysis Centers (IAACs) due to the differences in ionospheric modeling methods and selected tracking stations. In this study on the International GNSS Service’s (IGS) final GIM, the ionospheric total electron content (TEC) (from 243 global navigation satellite system (GNSS) monitoring stations around the world) and the ionospheric TEC (from the Jason-3 altimeter satellite) are selected as reference. By using these three references, we evaluate the performance and consistency of final GIM products from seven IGS IAACs, including the Chinese Academy of Sciences (CAS), the Center for Orbit Determination in Europe (CODE), Natural Resources Canada (EMR), the European Space Agency (ESA), the Jet Propulsion Laboratory (JPL), Universitat Politècnica de Catalunya (UPC), and Wuhan University (WHU) in the mid-solar activity year (2022) and the low-solar activity year (2020). Firstly, the comparison with the IGS final GIM shows that the consistency of each GIMs is basically the same, with the mean value ranging from −0.3 TECu (total electron content unit) to 1.4 TECu. Secondly, the validation with Jason-3 altimeter satellite shows that the accuracy of several GIMs is almost the same, except for the JPL with the worst accuracy and an overall mean deviation (BIAS) between 2 and 6 TECu. Thirdly, the comparison with VTEC extracted from GNSS monitor stations shows that the CAS has the best accuracy in different latitude bands with a root mean square (RMS) of about 2.2–4.7 TECu. In addition, it is found that the accuracy in areas with more stations for ionospheric modelling is better than those with less stations in different latitude bands; meanwhile, the accuracy is closely related to the modeling methods of different GIMs.

Ionospheric delay is one of the most problematic errors in single-frequency (SF) global navigation satellite system (GNSS) data processing. Global/regional ionospheric maps (GIM/RIM) are thus vitally important for positioning users. Given the coexistence of multi-GNSS, the integration of quad-constellation observations is essential for improving the distribution of ionospheric penetration points (IPPs) and increasing redundant observations compared with the existing GIM products from the IGS analysis center. In this paper, quad-constellation (GPS/GLONASS/Galileo/BDS) observations are applied to set up the RIM over Australia with uncombined precise point positioning (UC-PPP) and a low-order spherical harmonic function. The generated RIMs are then introduced to ionosphere-corrected (IC) and ionosphere-weighted (IW) single-frequency PPP (IC-SFPPP and IW-SFPPP) to verify their performance in terms of positioning accuracy and convergence time. Taking the CODE GIM as a reference, the results show that the mean root mean square (RMS) of VTEC differences is 0.867 TECUs, and the quad-constellation RIM (referred as ‘RIM4′) can improve the RMS of RIMs compared to single-constellation mode at the edge of regional experiment area. The application of the RIM4 in the BDS IC-SFPPP results in a 18.38% improvement (from 100.47 cm to 82.00 cm) of 3D positioning RMS compared to the CODE-GIMs, whereas 35.36% enhancement (from 115.92 cm to 74.62 cm) of 3D positioning RMS is achievable during an active ionospheric period. Moreover, if the criterion of the convergence time is defined as when positioning errors in the horizontal and vertical directions are less than 0.3 m and 0.6 m for 20 consecutive epochs, the IW-SFPPP can significantly speed up the convergence time compared to the uncombined SFPPP; that is, the convergence time is reduced by 52.7% (from 37 min to 17.5 min), 37.2% (from 72.5 min to 45.5 min), and 37.1% (from 62.0 min to 39.0 min) in the north, east and up direction, respectively, at the 68% confidence level.