Combining multi-source measurements can improve the accuracy and the spatial resolution of the three-dimensional (3-D) displacements field. Few researches have been conducted to integrate InSAR, GPS and leveling data of Tianjin in the recent three years to get the 3-D large displacement velocity field. How to effectively combine multi-source measurements and obtain the accurate 3-D large displacement field in high spatial resolution is worth studying. In this paper, the optimal method for acquiring 3-D displacement field by combining InSAR, leveling and GPS measurements is obtained by comparing the different methods. Then we realize the combining InSAR, leveling and GPS measurements to obtain the high-precision 3-D displacement field in Tianjin (China) from 2016 to 2018. Compared with different methods, we integrate InSAR, GPS and leveling measurements and use the weighted least squares method to estimate the 3-D displacement field with the highest accuracy. Although the accuracy of the horizontal displacement field obtained by this method has not been greatly improved, the vertical accuracy is obviously better than the other methods. The introduction of leveling measurements is beneficial to improve the accuracy of the vertical displacement field. Compared with independent GPS measurements, the standard deviations of 3-D displacements velocity field estimated by optimal solution method is 2.6 mm/yr, 2.1 mm/yr and 2.7 mm/yr in the vertical, eastern and northern directions, respectively. These results indicate that this method effectively utilizes the advantages of GPS, InSAR and leveling measurements, and extends the limitations of a single technical in describing surface-time scale applications. And the 3-D displacements information with a large spatial scale and high spatial resolution provides a reliable data basis for studying the crustal movement and its dynamic mechanism in China.

Satellite attitude modes and antenna phase center variations have a great influence on the Precise Orbit Determination (POD) of Low Earth Orbit satellites (LEOs). Inaccurate information about spacecraft attitude, phase center offsets and variations in the POD leads to orbital error. The Jason-3 satellite experienced complex attitude modes which are fixed, sinusoidal, ramp-up/down and yaw-flip. Therefore, it is necessary to properly construct the attitude model in the process of POD especially when there is no external attitude data. For the antenna phase center correction, the PCO which is the deviation between Antenna Reference Point (ARP) and Mean Antenna Phase Center (MAPC) usually can be calibrated on the ground accurately, but the PCV which is the deviation between Instantaneous Antenna Phase Center (IAPC) and Mean Antenna Phase Center (MAPC) will change greatly with the change of space environment. Residual approach can be used to estimate the receiver PCV map. In this paper, we collected the on-board GPS data of Jason-3 satellite from January 2019 and analyzed the impacts of PCV and spacecraft attitude on the orbit accuracy by performing the reduced-dynamic POD. Compared with the reference orbit released by the Centre National d'etudes Spatiales (CNES), using the PCV map can reduce the Root Mean Square (RMS) of orbit differences in the Radial (R), Along-track (T), Cross-track (N) and 3D direction about 0.3, 1.0, 0.9, and 1.4 mm. Based on the estimated PCV map, the orbit accuracy in R, T, N and 3D direction is 1.24, 2.81, 1.17, and 3.29 cm respectively by using the measured attitude data. When using the attitude model, the orbit accuracy in R, T, N and 3D directions is 1.60, 3.54, 1.33, and 4.13 cm, respectively. The results showed that the combination of measured attitude data and modeled PCV map can obtain the better orbit solution. It is essential to build a corresponding model in high-precision orbit determination, when there is no attitude data and PCV map.

Satellite laser ranging (SLR) observations provide an independent validation of the global navigation satellite system (GNSS) orbits derived using microwave measurements. SLR residuals have also proven to be an important indicator of orbit radial accuracy. In this study, SLR validation is conducted for the precise orbits of eight Galileo satellites covering four to eight years (the current longest span), provided by multiple analysis centers (ACs) participating in the multi-GNSS experiment (MGEX). The purpose of this long-term analysis (the longest such study to date), is to provide a comprehensive evaluation of orbit product quality, its influencing factors, and the effect of perturbation model updates on precise orbit determination (POD) processing. A conventional ECOM solar radiation pressure (SRP) model was used for POD. The results showed distinct periodic variations with angular arguments in the SRP model, implying certain defects in the ECOM system. Updated SRP descriptions, such as ECOM2 or the Box-Wing model, led to significant improvements in SLR residuals for orbital products from multiple ACs. The standard deviation of these residuals decreased from 8–10 cm, before the SRP update, to about 3 cm afterward. The systematic bias of the residuals was also reduced by 2–4 cm and the apparent variability decreased significantly. In addition, the effects of gradual SRP model updates in the POD were evident in orbit comparisons. Orbital differences between ACs in the radial direction were reduced from the initial 10 cm to better than 3 cm, which is consistent with the results of SLR residual analysis. These results suggest SLR validation to be a powerful technique for evaluating the quality of POD strategies in GNSS orbits. Furthermore, this study has demonstrated that perturbation models, such as SRP, provide a better orbit modeling for the Galileo satellites.

With the successful use of GPS-only-based POD (precise orbit determination), more and more satellites carry onboard GPS receivers to support their orbit accuracy requirements. It provides continuous GPS observations in high precision, and becomes an indispensable way to obtain the orbit of LEO satellites. Precise orbit determination of LEO satellites plays an important role for the application of LEO satellites. Numerous factors should be considered in the POD processing. In this paper, several factors that impact precise orbit determination are analyzed, namely the satellite altitude, the time-variable earth’s gravity field, the GPS satellite clock error and accelerometer observation. The GRACE satellites provide ideal platform to study the performance of factors for precise orbit determination using zero-difference GPS data. These factors are quantitatively analyzed on affecting the accuracy of dynamic orbit using GRACE observations from 2005 to 2011 by SHORDE software. The study indicates that: (1) with the altitude of the GRACE satellite is lowered from 480 km to 460 km in seven years, the 3D (three-dimension) position accuracy of GRACE satellite orbit is about 3∼4 cm based on long spans data; (2) the accelerometer data improves the 3D position accuracy of GRACE in about 1 cm; (3) the accuracy of zero-difference dynamic orbit is about 6 cm with the GPS satellite clock error products in 5 min sampling interval and can be raised to 4 cm, if the GPS satellite clock error products with 30 s sampling interval can be adopted. (4) the time-variable part of earth gravity field model improves the 3D position accuracy of GRACE in about 0.5∼1.5 cm. Based on this study, we quantitatively analyze the factors that affect precise orbit determination of LEO satellites. This study plays an important role to improve the accuracy of LEO satellites orbit determination.

The quality of Gravity Recovery and Climate Experiment (GRACE) observation is the prerequisite for obtaining the high-precision GRACE temporal gravity field model. To study the influence of new-generation GRACE Level-1B Release 03 (RL03) data and the new atmosphere and ocean de-aliasing (AOD1B) products on recovering temporal gravity field models and precise orbit determination (POD) solutions, we combined the global positioning system and K-band ranging-rate (KBRR) observations of GRACE satellites to estimate the effect of different data types on these solutions. The POD and monthly gravity field solutions are obtained from 2005 to 2010 by SHORDE software developed by the Shanghai Astronomical Observatory. The post-fit residuals of the KBRR data were decreased by approximately 10%, the precision of three-direction positions of the GRACE POD was improved by approximately 5%, and the signal-to-noise ratio of the monthly gravity field model was enhanced. The improvements in the new release of monthly gravity field model and POD solutions can be attributed to the enhanced Level-1B KBRR data and the AOD1B model. These improvements were primarily due to the enhanced of KBRR data; the effect of the AOD1B model was not significant. The results also showed that KBRR data slightly improve the satellite orbit precision, and obviously enhance the precision of the gravity field model.

The 2025 MW 7.0 Dingri earthquake in southern Tibet provides a unique opportunity to investigate normal-faulting mechanisms within an active rift zone. By integrating geodetic (GNSS and InSAR) and field observations, we investigate the event’s interseismic and coseismic deformation and quantify the impact of the 2015 MW 7.8 Gorkha earthquake. Our principal findings are: (1) The epicentral extensional strain rate is (1.5 ± 0.2) × 10-8/yr, notably lower than in the northern aftershock zone, indicating strain partitioning. (2) The coseismic slip model reveals a graben structure formed by two near N-S striking normal faults, with a maximum slip of 4.1 m and a seismic moment of 4.2×1019 N·m. (3) Field measurements confirm a segmented surface rupture, where the central segment’s vertical slip (2.1–2.2 m) aligns precisely with the InSAR-derived Line-of-Sight deformation maximum (2.04 m), validating the geodetic model. (4) Critically, deformation analysis demonstrates that the 2015 Gorkha earthquake significantly promoted the rupture of the Dingri earthquake, potentially accelerating its seismic cycle by ~20 years. This event exemplifies rift propagation along the Shenzha-Dingjie system and offers crucial insights into post-seismic stress transfer, rift evolution, and deep crustal processes in southern Tibet.