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We examine the decadal evolution of GPS, GLONASS, and Galileo satellite orbital elements, including the semi-major axis, inclination, eccentricity, right ascension of the ascending node, and the argument of perigee. We focus on the long-term changes in Keplerian elements by averaging them over several complete revolutions forming mean orbital elements giving an explanation of the main perturbing forces for each Keplerian parameter. The combined International GNSS Service (IGS) orbits are employed which were derived in the framework of IGS Repro3 for ITRF2020 preparation spanning eight years from 2013 to 2021. The semi-major axis for GPS satellites is affected by a strong resonance with Earth’s gravity field resulting in a long-period perturbation similar to a secular drift. The semi-major axes of Galileo and GLONASS do not show any large-scale rates, however, Galileo satellites are affected by the Y-bias resulting in semi-major axis drifts. A significant perturbations due to solar radiation pressure affect the semi-major axis, eccentricity, and the argument of perigee. Notably, for Galileo satellites in eccentric orbits, the signal with a one-draconitic year is evident in the semi-major axis. The evolution of the mean right ascension of the ascending node and argument of perigee is primarily characterized by nearly linear regression mainly due to even zonal harmonics of the Earth’s gravity field. The long-term evolution of eccentricity and inclination does not follow a linear trend but exhibits clear oscillations dependent on the secular drift of the right ascension of the ascending node (for inclination) or the argument of perigee (for eccentricity). Additionally, the long-term perturbation of inclination reaches its maximum when the absolute value of the Sun’s elevation angle above the orbital plane ( angle) is at its minimum, while the eccentricity reaches its minimum simultaneously with the minimum of the angle. [ABSTRACT FROM AUTHOR]

As its contribution to the latest release of the International Terrestrial Reference Frame, ITRF2020, the International GNSS Service (IGS) provided a 27-year-long series of daily “repro3” terrestrial frame solutions obtained by combining reprocessed solutions from ten Analysis Centers. This contribution represents an improvement over the previous contribution to ITRF2014, not only by the inclusion of more stations with longer and more complete position time series, but also by a general reduction in random and systematic errors. The IGS contribution to ITRF2020 also provided, for the first time, an independent estimate of the terrestrial scale based on the calibration of the Galileo satellite antennas. Despite the various observed improvements, the repro3 station position time series remain affected by a variety of random and systematic errors. This includes spurious periodic variations in several frequency bands, originating mostly from orbit and tide modeling errors, on top of a combination of white and flicker noise, whose origins remain to be precisely understood. These various components should carefully be accounted for when modeling GNSS station position time series and interpreting them in terms of Earth’s surface deformation. The Galileo-based scale of the repro3 solutions is found to be significantly offset (by + 4.3 mm at epoch 2015.0) and drifting (by + 0.11 mm/year) from the SLR/VLBI-based scale of ITRF2020. The reasons for this offset and drift remain to be uncovered. [ABSTRACT FROM AUTHOR]

The high-precision terrestrial reference frame, as the spatial benchmark for geodesy, is an important national infrastructure. However, due to the influence of nonlinear factors related to geophysical phenomena, the overall maintenance accuracy of the ITRF framework is still at the centimeter level. Therefore, accurately characterizing the true trajectories of linear motion, nonlinear motion, and geocentric motion of the reference station is the key to achieve the construction and maintenance technology of a millimeter level terrestrial reference framework. Based on long-term global and regional GNSS observation data, more Chinese geodesy scientists devoted much efforts to the maintenance of millimeter-level geodetic reference framework. The main contributions of this work included the followings: ①Dynamic maintenance of millimeter-level terrestrial reference frame;②Research progress on the method of maintenance of regional reference frame based on GNSS; ③The progress of CGCS2000 frame maintenance in millimeter level accuracy; ④Reprocessing and reanalysis of two-decade GNSS observation in continental China; ⑤Research on current GNSS velocity field model and deformation in Chinese mainland; ⑥The preliminary realization and evaluation of CTRF2020.

In preparation for the International Terrestrial Reference Frame 2020, the International GNSS Service analysis centers released the results of the third reprocessing campaign (IGS Repro 3) of all the GNSS network solutions backwards starting from 1994. For the first time, the IGS reprocessing products included not just GPS and GLONASS, but also the Galileo constellation. In this study, we describe the methodology and results of the orbit combination provided by the IGS Analysis Center Coordinator (IGS ACC) at Geoscience Australia. The quality of the combined orbit products was cross-checked with the individual IGS Repro3 Analysis Center (AC) contributions. The internal consistency of the individual Analysis Center (AC) solutions with the combined orbits was assessed based on the root mean square of the 3D orbit differences. In 2020, the mean consistency of the combination is at the level of 9, 23, and 15 mm for GPS, GLONASS, and Galileo, respectively. The external validation of the orbits was performed using Satellite Laser Ranging (SLR). We proposed a novel approach to handling detector-specific biases in the results of SLR validation, which reduced the standard deviation of SLR residuals by up to 13% for Galileo FOC satellites. This method is based on bias aligning the offsets to single-photon SLR stations that were treated as a reference. The proposed approach increased the internal consistency of the SLR dataset, facilitating the detection of orbit modeling issues. The standard deviation of SLR residuals of the best individual solution versus the combined solution equals 13/13, 15/17, 17/17, 18/19 mm for Galileo-FOC, -IOV, GLONASS-K1B, -M, respectively. Therefore, the combined solution can be considered equal in quality compared to the best individual AC solutions. Searching for patterns in SLR residuals for different satellite-Sun-Earth geometries revealed that some orbit modeling issues are not fully diminished for individual ACs. Eventually, our findings suggest that the delivered combined orbit product may be considered the best solution overall, as it benefits from the best individual solutions for each satellite type. [ABSTRACT FROM AUTHOR]

Extensive data collection, unified and rigorous data processing, and accurate construction of station motion model (especially the correction of co-seismic/post-seismic effects of large earthquakes) are three basic elements for the accuracy and reliability of Global Navigation Satellite System (GNSS) velocity. Thus, we take advantage of the sensitivity features of the spectral analysis and hypothesis test to refine the site movement trajectory model, and apply it to the reprocessed GNSS three-decade coordinate time series. Firstly, we reprocess GNSS observations and seismic records based on the updated convention and processing settings of International GNSS Service (IGS) repro3. Secondly, we use the Improved Lomb–Scargle Periodogram (ILSP) model to analyze the periodic characteristics of GNSS vertical time series. The results represent that the primary period of about 35% of sites is 365 days, and the secondary period of 20% of sites is 182 days. Thirdly, we evaluate the performance of different time series model component combination of the time series (a: velocity only; b: velocity + offset; c: velocity + offset + PSD; d: velocity + offset + PSD + period) and Post-Seismic Deformation (PSD) modes (PSD1: None; PSD 2: Exp; PSD 3: Log; PSD 4: Exp + Log). Fourthly, we use the chi-square test to assess the overall correctness of the trajectory model, followed by the t -test to test the significance of each parameter further, and then use the optimized model to refit and reanalyze GNSS time series. The analysis of the velocity results illustrates that the fitting accuracy of GNSS time series is 3–6 mm in the horizontal direction and 4–9 mm in the vertical direction. Lastly, we obtain a refined global three-dimensional velocity field based on GNSS three-decade time series, with the median velocity of Root Mean Square Error (RMSE) as 0.17, 0.17, and 0.32 mm/a in N/E/U direction. Compared with ITRF2014, the velocity difference is at 1–2 mm/a level due to differences in GNSS observations, trajectory model, and geodetic technology. [ABSTRACT FROM AUTHOR]

Extensive observation collection, unified and rigorous data processing, and accurate construction of the station motion model are the three essential elements for the accuracy and reliability of the Global Navigation Satellite System (GNSS) velocity field. GNSS data reprocessing not only can weaken the influence of untrue nonlinear site signals caused by imperfect models but also can eliminate the displacement offset caused by frame transformation, solution strategy, and model change. Based on the new repro3 criteria of the International GNSS Service (IGS), we process rigorously GNSS observations of continental China from the period 2000 to 2020 to refine GNSS station secular velocities and analyze the present-day crustal deformation in continental China. The main contributions of this work included the followings. Firstly, the repro3 algorithm and model are used to uniformly and rigorously process the two-decade GNSS historical observations to obtain more reliable GNSS coordinate time series with mm-level precision. Combined with the historical records of major earthquakes in continental China, we build a GNSS time series model considering nonlinear factors (velocity, offset, period, co-seismic/post-seismic deformation) to extract GNSS horizontal velocity field whose root mean square (RMS) mean is 0.1 mm/a. Secondly, the GNSS horizontal grid velocity field in continental China is interpolated using the gpsgridder method (the minimum radius is set to 16, and the Poisson's ratio is set to 0.5). Estimation and analysis of the crustal strain rate solution lead to the conclusion that the strain degree in West China (the high strain region is mainly located in the Qinghai Tibet Plateau and Tianshan Mountains) is much more intense than that in the east (the main strain rate is less than 5 nstrain/year). In addition, most strong earthquakes in the Chinese mainland occurred on active blocks and their boundary faults with large changes in the GNSS velocity field and strain field. Then, an improved K-means++ clustering analysis method is proposed to divide active blocks using GNSS horizontal velocity field. Furthermore, different relative motion models of different blocks are constructed using the block division results. Among them, the Eurasian block has the lowest accuracy (the RMS of residual velocity in the east and north directions are 5.60 and 9.65 mm/a, respectively), and the China block 7 has the highest accuracy (the RMS mean of relative velocity in the east and north directions are 2.60 and 2.65 mm/a, respectively). More observations (2260+ sites), longer time (20 years), and updated criteria (Repro3) are to finely obtain the GNSS velocity field in continental China, and depict crustal deformation and active block with the gpsgridder and improved K-means++ methods. [ABSTRACT FROM AUTHOR]

Extensive observation collection, unified and rigorous data processing, and accurate construction of the station motion model are the three essential elements for the accuracy and reliability of the Global Navigation Satellite System (GNSS) velocity field. GNSS data reprocessing not only can weaken the influence of untrue nonlinear site signals caused by imperfect models but also can eliminate the displacement offset caused by frame transformation, solution strategy, and model change. Based on the new repro3 criteria of the International GNSS Service (IGS), we process rigorously GNSS observations of continental China from the period 2000 to 2020 to refine GNSS station secular velocities and analyze the present-day crustal deformation in continental China. The main contributions of this work included the followings. Firstly, the repro3 algorithm and model are used to uniformly and rigorously process the two-decade GNSS historical observations to obtain more reliable GNSS coordinate time series with mm-level precision. Combined with the historical records of major earthquakes in continental China, we build a GNSS time series model considering nonlinear factors (velocity, offset, period, co-seismic/post-seismic deformation) to extract GNSS horizontal velocity field whose root mean square (RMS) mean is 0.1 mm/a. Secondly, the GNSS horizontal grid velocity field in continental China is interpolated using the gpsgridder method (the minimum radius is set to 16, and the Poisson’s ratio is set to 0.5). Estimation and analysis of the crustal strain rate solution lead to the conclusion that the strain degree in West China (the high strain region is mainly located in the Qinghai Tibet Plateau and Tianshan Mountains) is much more intense than that in the east (the main strain rate is less than 5 nstrain/year). In addition, most strong earthquakes in the Chinese mainland occurred on active blocks and their boundary faults with large changes in the GNSS velocity field and strain field. Then, an improved K-means++ clustering analysis method is proposed to divide active blocks using GNSS horizontal velocity field. Furthermore, different relative motion models of different blocks are constructed using the block division results. Among them, the Eurasian block has the lowest accuracy (the RMS of residual velocity in the east and north directions are 5.60 and 9.65 mm/a, respectively), and the China block 7 has the highest accuracy (the RMS mean of relative velocity in the east and north directions are 2.60 and 2.65 mm/a, respectively). More observations (2260+ sites), longer time (20 years), and updated criteria (Repro3) are to finely obtain the GNSS velocity field in continental China, and depict crustal deformation and active block with the gpsgridder and improved K-means++ methods.