The International GNSS Service (IGS) real-time service (RTS) provides access to real-time precise products such as orbits, clocks and code biases, which can be used as a substitute for ultra-rapid products in real-time applications. The true performance of these products can be assessed by the Analysis Centers daily statistics derived from the comparison with IGS rapid products. Additionally, indirect verification is performed by their application to various precise point positioning strategies. Monitoring results and basic descriptions of these products are available at the official RTS Web page (http://rts.igs.org/). We present a more detailed description of RTS products. Information from various sources is collected to provide products application methodology and describe their important features. We provide extended verification of the products using 1 week of real-time correction data. Results are presented separately for GNSS constellations, considering satellite block and type of onboard clock. Comparison with ESA/European Space Operations Centre final products proves the high accuracy of RTS orbits and clocks, which is 5 cm for GPS orbits, 8 cm for GPS clocks, 13 cm for GLONASS orbits and 24 cm for GLONASS clocks. The real-time correction performance is also examined regarding availability and latency. In general, the availability of corrections was beyond 95 % for GPS and beyond 90 % for GLONASS. Since the increasing degradation of product quality with latency is critical for real-time applications, the relation between product latency and accuracy is analyzed. It confirms that high-rate stream update intervals are suitable for the data provided and that the obsolete data should not be used. To avoid this, we propose a method of short-term prediction of RTS corrections that extends the application period of obsolete correction data without a significant loss in orbit quality. Using polynomial fitting, it is possible to forecast the orbit corrections reliably up to 8 min for GPS and 4 min for GLONASS.

An increasing number of satellites of global navigation satellite systems (GNSS) and their constant modernization allow improving positioning accuracy and enable performing the GNSS measurements in challenging environments. Since 2016, the Centre National d’Études Spatiales (CNES) has been providing real-time corrections for all GNSS and thus allows for the actual multi-GNSS precise point positioning in real time without any issues associated with the latency of orbit and clock products as in the case of the IGS final products. We provide a comprehensive evaluation of the availability and the quality of multi-GNSS real-time orbit and clock products through the comparison to the final Center for Orbit Determination in Europe (CODE) orbits, fitting long continuous orbital arcs, analyzing the orbit position differences with respect to satellite laser ranging observations, as well as the assessment of clock stability using modified Allan deviation diagrams. The 3D orbit RMS over a 1-month test period, when compared to CODE products, is 5, 10, 18, 18 and 36 cm for GPS, GLONASS, Galileo, BeiDou MEO and BeiDou IGSO, respectively. The error of BeiDou geostationary orbits is above the 1-m level. Finally, we found that the quality of orbits and clocks is a function of the satellite system, orbital plane and the elevation of the Sun above the orbital plane, the satellite altitude, as well as the satellite block and generation.

In GNSS data processing, the station height, receiver clock and tropospheric delay (ZTD) are highly correlated to each other. Although the zenith hydrostatic delay of the troposphere can be provided with sufficient accuracy, zenith wet delay (ZWD) has to be estimated, which is usually done in a random walk process. Since ZWD temporal variation depends on the water vapor content in the atmosphere, it seems to be reasonable that ZWD constraints in GNSS processing should be geographically and/or time dependent. We propose to take benefit from numerical weather prediction models to define optimum random walk process noise. In the first approach, we used archived VMF1-G data to calculate a grid of yearly and monthly means of the difference of ZWD between two consecutive epochs divided by the root square of the time lapsed, which can be considered as a random walk process noise. Alternatively, we used the Global Forecast System model from National Centres for Environmental Prediction to calculate random walk process noise dynamically in real-time. We performed two representative experimental campaigns with 20 globally distributed International GNSS Service (IGS) stations and compared real-time ZTD estimates with the official ZTD product from the IGS. With both our approaches, we obtained an improvement of up to 10% in accuracy of the ZTD estimates compared to any uniformly fixed random walk process noise applied for all stations.

The tropospheric delay is one of the major error sources in precise point positioning (PPP), affecting the accuracy and precision of estimated coordinates and convergence time, which raises demand for a reliable tropospheric model, suitable to support PPP. In this study, we investigate the impact of three tropospheric models and mapping functions regarding position accuracy and convergence time. We propose a routine to constrain the tropospheric estimates, which we implemented in the in-house developed real-time PPP software. We take advantage of the high spatial resolution (4 × 4 km²) numerical weather prediction Weather Research and Forecasting (WRF) model and near real-time GNSS data combined by the least-squares collocation estimation to reconstruct the tropospheric delays. We also present mapping functions calculated from the WRF model using the ray-tracing technique. The performance tests are conducted on 14 Polish EUREF Permanent Network (EPN) stations during 3 weeks of different tropospheric conditions: calm, standard and severe. We consider six GNSS data processing variants, including two commonly used variants using a priori ZTD and mapping functions from UNB3m and VMF1-FC models, one with a priori ZTD and mapping functions calculated directly from WRF model and three variants using the aforementioned mapping functions but with ZTD model based on GNSS and WRF data used as a priori troposphere and to constrain tropospheric estimates. The application of a high-resolution GNSS/WRF-based ZTD model and mapping functions results in the best agreement with the official EPN coordinates. In both static and kinematic modes, this approach results in an average reduction of 3D bias by 20 and 10 mm, respectively, but an increase of 3D SDs by 1.5 and 4 mm, respectively. The application of high-resolution tropospheric model also shortens the convergence time, for example, for a 10 cm convergence level, from 67 to 58 min for the horizontal components and from 79 to 63 min for the vertical component.

Global navigation satellite system (GNSS) remote sensing of the troposphere, called GNSS meteorology, is already a well-established tool in post-processing applications. Real-time GNSS meteorology has been possible since 2013, when the International GNSS Service (IGS) established its real-time service. The reported accuracy of the real-time zenith total delay (ZTD) has not improved significantly over time and usually remains at the level of 5–18 mm, depending on the station and test period studied. Millimeter-level improvements are noticed due to GPS ambiguity resolution, gradient estimation, or multi-GNSS processing. However, neither are these achievements combined in a single processing strategy, nor is the impact of other processing parameters on ZTD accuracy analyzed. Therefore, we discuss these shortcomings in detail and present a comprehensive analysis of the sensitivity of real-time ZTD on processing parameters. First, we identify a so-called common strategy, which combines processing parameters that are identified to be the most popular among published papers on the topic. We question the popular elevation-dependent weighting function and introduce an alternative one. We investigate the impact of selected processing parameters, i.e., PPP functional model, GNSS selection and combination, inter-system weighting, elevation-dependent weighting function, and gradient estimation. We define an advanced strategy dedicated to real-time GNSS meteorology, which is superior to the common one. The a posteriori error of estimated ZTD is reduced by 41%. The accuracy of ZTD estimates with the proposed strategy is improved by 17% with respect to the IGS final products and varies over stations from 5.4 to 10.1 mm. Finally, we confirm the latitude dependency of ZTD accuracy, but also detect its seasonality.