With the rapid development of Global Navigation Satellite System (GNSS) technology, the long-term accumulated GNSS observations of global reference stations have provided valuable data for geodesy and geodynamics studies since the 1990s. Acquiring the precise velocity of GNSS stations is very important for the study of global plate movement, crustal deformation, etc. However, the seismic activities nearby some GNSS observation stations may seriously change the station’s motion trajectory. Therefore, our research was motivated to propose a method allowing for station seismic deformation, and apply it to construct an updated global GNSS velocity field. The main contributions of this work included the following. Firstly, we improved the GNSS data processing procedures and seismic data selection strategies to obtain GNSS coordinate time series with mm-level precision (3–5 and 6–8 mm in the horizontal and vertical, respectively) and information of each site impacted by seismic events, which provides necessary input data for further analysis. Secondly, an Integrated Time Series Method (ITSM) concerning the effect of seismic deformation was proposed to model the station’s nonlinear motion accurately. Distinguished with existing studies, all parameters including seismic relaxation time can be simultaneously estimated by ITSM, which improves the accuracy and reliability of GNSS station velocity significantly. Thirdly, to optimize the ITSM-based model, the influences of seismic relaxation time (a. 0.1 × true, b. 10 × true, c. true), parameterization mode (a. Offset + Velocity, b. Offset + Velocity + PSD, c. Offset + Velocity + PSD + Period), and the Post-Seismic Deformation (PSD) model (a. None, b. Exp, c. Log, d. Exp + Log) on results of GNSS time series analyzing were discussed. The results showed that the fitting accuracy of GNSS displacements was better than 5 mm and 10 mm in the horizontal and vertical, respectively. Finally, the global GNSS station velocity field (referred to as GGV2020 hereafter) was refined by ITSM using global GNSS observations and seismic data during 1990–2020. This not only helps interpret plate tectonic motion, establish and maintain a Dynamic Terrestrial Reference Frame (DTRF) but also contributes to better investigating geodynamic processes. GGV2020 results showed that the accuracy of global velocity was better than 1 mm/a, and the averages of Root Mean Square Error (RMSE) were 0.19 mm/a, 0.19 mm/a, and 0.33 mm/a in the north, east, and up direction, respectively. Besides, the RMSE obeys normal distribution. Compared with ITRF2014, there was a difference of about 1–2 mm/a between them due to differences in terms of observation span, processing model, and geodetic technology. Moreover, GGV2020 is expected to enrich and update the existing velocity field products to describe the characteristics of regional crustal movement in more detail, especially in Antarctica.

In this paper, we propose a method for the analysis of tectonic movement and crustal deformation by using GNSS baseline length change rates or baseline linear strain rates. The method is applied to daily coordinate solutions of continuous GNSS stations of the Crustal Movement Observation Network of China (CMONOC). The results show that: (a) The baseline linear strain rates are uneven in space, which is prominent in the Tianshan, Sichuan-Yunnan, Qinghai-Tibet Plateau, and Yanjing areas, with a maximum value of 1 × 10⁻⁷ a⁻¹, and about two orders smaller in the South China block, the Northeast block, and the inner area of the Tarim basin, where the average baseline linear strain rates are 1.471 × 10⁻⁹ a⁻¹, 2.242 × 10⁻⁹ a⁻¹, and 3.056 × 10⁻⁹ a⁻¹, respectively; (b) Active crustal deformation and strong earthquakes in the Xinjiang area are mainly located in the north and south sides of the Tianshan block; the compression deformations both inside the Tarim block and in the southern Tianshan fault zone are all increasing from east to west, and the Tarim block is not a completely “rigid block”, with the shrinkage rate in the west part at about 1~2 mm/a; (c) The principal directions of crustal deformation in the Xinjiang, Tibet, and Sichuan-Yunnan regions are generally in the north—south compression and east—west extension, indicating that the collision and wedging between the Indian and Eurasian plates are still the main source of tectonic movements in mainland China.

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.

The ionospheric delay is one of the important error sources in the Global Navigation Satellite System (GNSS) data processing. With the rapid construction and development of GNSS, the abundant satellite resources have brought new opportunities for ionospheric monitoring. To further investigate the performances and abilities of Galileo and BDS in ionosphere modeling, we study the ionosphere modeling based on the 15th order spherical harmonic function, and 364 stations around the world are selected for global ionospheric modeling of GPS, GLONASS, Galileo and BDS systems under ionospheric quiet and active conditions, respectively. The results show that the average biases of the ionospheric models built by GPS, GLONASS and Galileo are relatively small, which are within 2 Total Electron Content Unit (TECU) as compared to the Center for Orbit Determination in Europe (CODE) global ionospheric map (GIM), while the average biases of the models built by BDS are between 6 and 8 TECU during the ionospheric quiet and active days, respectively. In addition, in order to analyze the modeling performances before and after using BDS geostationary earth orbit (GEO) satellites, BDS is divided into two groups, in which one group contains medium earth orbit (MEO), inclined geosynchronous orbit (IGSO) and GEO satellites; and the other group contains only MEO and IGSO satellites. The results show that the influence of GEO satellites on ionospheric modeling is less than 1 TECU. Due to the distribution of the stations, the 0-value region in the ionospheric model is mainly distributed in the mid and high-latitude regions of the southern hemisphere. Since the ionospheric parameters are lumped with the Differential Code Bias (DCB), we also estimate the DCB parameters and analyze their performances. The DCB estimated in ionosphere modeling shows strong stability, with the average biases of GPS, GLONASS, Galileo and BDS under 0.25 ns, 0.25 ns, 0.2 ns and 0.42 ns, respectively. We also estimate other DCB types of the four GNSS systems. The results show that the DCB is stable and shows consistency with Chinese Academy of Sciences (CAS) DCB products.

The quality of satellite clock offset affects the performances of positioning, navigation and timing services, and thus it is essential to the Global Navigation Satellite System (GNSS). This research focuses on the estimation of BeiDou Navigation Satellite System (BDS) real-time precise satellite clock offset by using GNSS stations located in the Global and Asia-Pacific region based on the mixed-difference model. The precision of the estimated BDS clock corrections is then analyzed with the classification of the orbit types, satellite generations, and atomic clock types. The results show that the precision of the BDS clock offset estimated in the Asia-Pacific for Geosynchronous Earth Orbit (GEO), Inclined Geosynchronous Satellite Orbit (IGSO) and Medium Earth Orbit (MEO) satellites are 0.204 ns, 0.077 ns and 0.085 ns, respectively, as compared to those of clock offsets estimated in globally distributed stations. The average precision of the BDS-3 satellites clock offset estimated in global region is 0.074 ns, which is much better than the 0.130 ns of BDS-2. Furthermore, analyzing the characteristics of the corresponding atomic clocks can explain the performance of the estimated satellite clock offset, and the stability and accuracy of various parameters of the Passive Hydrogen Maser (PHM) atomic clocks are better than those of Rubidium (Rb) atomic clocks. In the positioning domain, the real-time clocks estimated in the global/Asia-Pacific have been applied to BDS kinematic Precise Point Positioning (PPP) in different regions. The Root Mean Square (RMS) of positioning results in global real-time kinematic PPP is within 4 cm in the horizontal direction and about 6 cm in the vertical direction. Hence, the BDS real-time clock offset can supply the centimeter-level positioning demand around the world.

The current international and regional reference frame research is mainly realized by single GPS (Global Position System) technology. With the full deployment of BDS (Beidou Navigation System), it is urgent to study and establish the corresponding terrestrial reference frame. Since 2019, the global and regional BDS service performance has been evaluated and tested, and the long-term BDS observations of MGEX (Multi GNSS Experiment) sites distributed worldwide provide the possibility for the preliminary construction of the BDS terrestrial reference frame. We aim to preliminarily realize and evaluate the CTRF2020 (COMPASS/BDS Terrestrial Reference Frame at the epoch of 2020.0) that can be expressed with the coordinates and velocities of a series of reference sites at the epoch of 2020.0. Firstly, the actual BDS global service performance evaluation reflects BDS satellite's high visibility and change trend in recent three years, which provides primary input data for the frame. Then, the BDS observations of about 100 global sites in the recent three years are calculated by PPP (Precise Point Positioning) and NET solution, to obtain the global high-precision BDS coordinate time series. Then, the BDS time series of the two solutions are fitted and compared with the IGS14 velocity field. The results show that the series accuracy of PPP-BDS and NET-BDS solutions is equivalent, and there is an mm-level systematic deviation with IGS14 solutions. The horizontal series fitting accuracy of PPP-BDS and NET-BDS solutions is better than that of the vertical direction, the accuracy of NET-BDS solution is slightly better than PPP-BDS, and the difference of fitting accuracy is 0.12, 0.13, and 0.50 mm in the NEU direction. The velocity field accuracy of PPP-BDS and NET-BDS solution is the same, and the overall three-dimensional velocity difference is less than 0.2 mm/a. The velocity fields of PPP-BDS and NET-BDS solution have little difference from IGS14, and the overall difference is less than 0.5 mm/a. Finally, we give the limitations and improvement points of CTRF2020. The preliminary realization and evaluation of CTRF2020 may be expected to provide a reference for the future realization of a comprehensive terrestrial reference framework dominated by BDS technology and supplemented by multi-source space geodetic technology.