This study employs time-series InSAR technology to extract the interseismic surface deformation field along the Anninghe-Zemuhe fault zone on the eastern margin of the Sichuan-Yunnan rhombic block. We further invert the interseismic slip rates and locking depths of the fault system. Key findings include: the cross-fault InSAR deformation velocity gradient along the Anninghe fault increases progressively from ~2 mm/a in the northern segment to ~2.5 mm/a in the southern segment, whereas the Zemuhe fault exhibits a relatively smaller gradient of ~1.8 mm/a.Slip rates along the Anninghe fault vary spatially: ~2.8 mm/a at the northern Shimian segment, ~4.0 mm/a at the central Mianning segment, and ~3.2 mm/a at the southern Xichang segment. The Zemuhe fault shows a decreasing slip rate from ~3.1 mm/a in the northern segment to ~2.6 mm/a in the southern Ningnan segment.Locking depth analysis reveals maximum values (~37.8 km) beneath the Xichang segment, gradually shallowing northward to ~5.0 km at Shimian and southward to ~13.2 km at Ningnan.These results demonstrate that the Xichang segment, characterized by higher slip rates and deeper locking depths, exhibits enhanced seismic potential, consistent with its historically dense seismicity. This spatial correlation between geodetic deformation patterns and seismic activity provides critical insights into strain accumulation processes within this active tectonic boundary.

Based on the PWV time series data inverted from GPS during 2010-2018 and the PWV data calculated from the ERA5 reanalysis data for the same period, a combination of the generative adversarial networks(GAN) model and the Transformer neural network model in deep learning was employed to achieve short-term forecasting of PWV in Greenland using GPS-PWV data. The prediction results were evaluated using the ERA5 data from 2019. The results show that the model performed well in most areas, with a root mean square error(RMSE) better than 4.5 mm and a correlation coefficient greater than 0.7. The correlation coefficients in spring, autumn, and winter were all above 0.5, while in summer, the correlation coefficients on some dates were slightly lower due to severe weather changes. This method is capable of predicting the spatial distribution and temporal variations of PWV in Greenland.

By dividing the seismic cycles of M_S≥7.8 earthquakes in China's mainland and adjacent regions and studying the migration of main active zones, combined with the acceleration-deceleration changes of Earth's rotation speed, this study explores the spatiotemporal patterns and driving mechanisms of M8.0 seismic activity in the study area. The main conclusions are as follows: 1) Since 1879, the study area has experienced 6 active periods of M8.0 earthquakes. The second active period mainly occurred in the Pamir-Baikal seismic belt, the third in the northeastern margin of the Qinghai-Xizang plateau, the fourth in the southeastern margin, the fifth in Yunnan and north China, and the sixth around the Bayan Har block within the Qinghai-Xizang plateau. The region may currently be in the initial stage of a new active period. 2) Since 1867, Earth's length of day(LOD) variation curve shows 4 acceleration-deceleration cycles and 16 acceleration-deceleration phases. The superposition of S tectonic stress fields with deceleration changes favors M8.0 earthquakes in the Pamir-Baikal belt, while NE-oriented stress fields combined with acceleration changes facilitate M8.0 earthquakes along the Qinghai-Xizang plateau margins and interior. The transition from acceleration to deceleration phases causes the tectonic stress field around the Qinghai-Xizang plateau to shift from NE-dominated to locally restored NS orientation, serving as the main driver for the third, fourth, and sixth active periods. 3) The tectonic stress field in China's mainland and adjacent regions has experienced clockwise rotation from NS to NE and then to NEE orientations over the past century, potentially related to Earth's rotation changes involving significant deceleration before 1913 followed by overall acceleration. This process remains ongoing, with no current signs of concentrated M8.0 earthquakes similar to the second active period. However, vigilance is needed regarding possible continued NEE rotation of the Qinghai-Xizang plateau's stress field, and future emergence of new main active zones cannot be ruled out.

Based on the P-wave travel-time data of 2 538 earthquake events(M_L≥1.0) recorded by 198 fixed stations of CENC from 2019 to 2023, the three-dimensional velocity structure of the crust in this area is inversed by double-difference tomography, earthquake relocation via double-difference tomography and waveform cross-correlation for enhanced accuracy and reliability, it reveals the coupling relationship between crustal structural heterogeneity and seismic activity under the background of craton destruction. The results show that after relocation, the root-mean-square(RMS) of seismic travel time residuals is reduced from 1.09 s to 0.52 s, and the residual average is optimized from －0.33 s to 0.02 s, the accuracy of the velocity model has been improved. Set four profile lines distributed in the Shanxi Jinzhong fault zone, Yanshan structural zone, Tangshan fault zone, Xingtai-Handan fault zone and other fault zones where earthquake events are more concentrated. Velocity structure analysis reveals that most seismic events are clustered within transitional zones between high- and low-velocity anomalies, the crustal thickness exhibits significant lateral heterogeneity. In the volcanic rift basin of Datong, Shanxi province, enhanced thermal-chemical upwelling corresponds to prominent low-velocity anomalies. The Yanshan tectonic zone displays alternating low-velocity and high-velocity anomalies, reflecting unstable stress conditions and structural anisotropy. Multiple strong earthquakes along the Tangshan fault zone predominantly occur within transitional zones between high-velocity and low-velocity anomalies. The Xingtai-Handan fault zone demonstrates concentrated seismic events likely triggered by lithospheric delamination processes associated with high-velocity anomalies.The dynamic mechanism of the destruction of the North China Craton is jointly dominated by lithospheric delamination, thermochemical erosion, and mantle convective erosion induced by the subduction of the Pacific plate, providing new geophysical constraints for understanding the stability evolution of the craton and the mechanism of strong earthquake propagation.

Based on observation data from 77 GNSS stations worldwide, this study systematically evaluates the global applicability of four tropospheric delay mapping function models(GMF, NMF, VMF1, VMF3) and their impact on the accuracy of precise point positioning(PPP). The zenith tropospheric delay(ZTD) for each station was obtained using the PRIDE PPP-AR software. With the ZTD products released by the Center for Orbit Determination in Europe(CODE) as a reference, a comparative analysis of model performance was conducted across geographical zones(low/medium/high latitudes, land/ocean, and altitude gradients). The results indicate that the existing tropospheric delay mapping function models exhibit poorer accuracy in low-latitude, low-altitude, and oceanic regions. The VMF series mapping function models perform better in addressing differences arising from changes in altitude and latitude, and both the GMF and VMF series models show significant correction effects for oceanic stations. In terms of positioning accuracy in the U direction, the GMF, VMF3, and NMF mapping function models perform best in low-latitude, medium-latitude, and high-latitude regions, respectively. Overall, the GMF and VMF series mapping function models demonstrate superior performance in global PPP data processing.

Based on continuous GNSS observation data, a relatively comprehensive three-dimensional GNSS velocity field for the northeastern margin of the Qinghai-Xizang plateau was established by fully considering random noise and regional environmental loading. This study characterizes crustal strain and vertical motion patterns in the research area. Results show that the region is dominated by compressive strain, with significant differences in principal strain rates between its southwestern and northeastern sectors. Notable distributions of maximum shear strain and principal strain are observed along the east Kunlun fault and Xianshuihe fault. Vertical uplift predominates across the northeastern Qinghai-Xizang plateau, suggesting that vertical tectonic forces may originate from intra-block compressional shortening or obstruction of deep lithospheric material flow. However, significant surface subsidence near the Lanzhou area is likely attributed to collapsible loess and soil erosion. Finally, estimates based on an incompressible Earth model indicate minimal vertical deformation caused by horizontal compression, implying that large-scale uplift in the northeastern Qinghai-Xizang plateau may primarily result from vertical tectonic factors such as lower crustal flow and lithospheric convective thinning, rather than horizontal crustal shortening.

To assess the accuracy of Earth rotation parameters(ERP) derived from the current VLBI global observing system(VGOS) observational data, this paper processes data from VGOS observations made between 2019 and 2023. Simultaneously, traditional S-band and X-band VLBI observational data, which were obtained during the same periods as the VGOS data, were also included in the processing. The EOP 14 C04 series provided by the IERS were used as reference values for accuracy assessment. The results show that, during the selected experimental data periods, the average weighted root mean square(WRMS) of the post-fit residuals of time delay from VGOS observational data is 16.77 ps, which is significantly better than the 30.97 ps from the traditional S/X VLBI measurements during the same periods. In terms of ERP determination, there are still differences between the results from global network station observational data of VGOS and traditional S/X VLBI. Specifically, the ERP polar motion component accuracy derived from VGOS is inferior to that of traditional S/X VLBI, while the UT1-UTC accuracy is comparable to that of traditional S/X VLBI measurements. Further analysis using experimental stations centered on co-located stations indicates that VGOS measurements can provide ERP determination results with higher accuracy.

Using Sentinel-1A data, this study employed D-InSAR technology to obtain the line-of-sight (LOS) co-seismic deformation field of the M_S6.8 earthquake in Dingri, Xizang, on January 7, 2025. The geometric parameters of the seismogenic fault were derived through a Bayesian approach. Fault slip distribution was inverted using the SDM, and co-seismic Coulomb stress changes were calculated. The inversion results indicate that the seismogenic fault has a strike of 187.34°, a dip angle of 56.40°, with an epicenter located at 87.50°E and 28.64°N, at a depth of 6.81 km. The maximum slip in the co-seismic slip distribution is 4.24 m, with an average rake angle of-58.82°, suggesting that the earthquake was predominantly a normal faulting event with a minor component of left-lateral strike-slip. The inverted moment magnitude is M_W7.0, and the seismogenic fault is preliminarily identified as the Dengmo Co fault. Additionally, regions along the Zanda-Lhazê-Qiongduojiang fault, Darjeeling-Ngamring-Rinbung fault, and parts of the south xizang detachment system fault, as well as the southern sections of the Xainza-Dingjie fault and Dengmo Co fault, exhibit Coulomb stress increases exceeding 0.1 bar, indicating that these areas warrant greater attention for future seismic hazards.

To address the issues of large pseudorange measurement noise, discontinuous observation data, weak geometric strength in smartphone GNSS observations, and high noise levels in the built-in micro inertial measurement unit(MIMU) of smartphones, a tightly coupled GNSS/MIMU navigation method enhanced by low-Earth orbit(LEO) satellites is proposed. Based on the characteristics of the Walker constellation and the Keplerian orbital parameters of LEO satellites, LEO pseudorange observation data are simulated. The positioning performance of smartphone GNSS single-point positioning, GNSS/MIMU tight integration, and LEO-enhanced GNSS/MIMU tight integration are compared and analyzed. Real smartphone data are used for validation. The experimental results show that after incorporating LEO satellites, the average number of visible satellites increases by about 7. The faster movement speed of LEO satellites further optimizes the GNSS geometric strength, reducing the average PDOP value by 50%. Compared with GNSS single-point positioning, the GNSS/MIMU tight integration improves positioning accuracy in the east, north, and up directions by 18%, 23%, and 10%, respectively. The LEO-enhanced GNSS/MIMU tight integration improves positioning accuracy in the east, north, and up directions by 73%, 81%, and 60% compared with GNSS single-point positioning, and by 67%, 75%, and 56% compared with GNSS/MIMU tight integration.

Applying the structural-stratigraphic analysis method, the shallow seismic profile across the fault in southwestern Haizhou depression is interpreted through borehole constraints. On this basis, five important structural interfaces of Yongji subsection of Haizhou section of northern Zhongtiaoshan fault are traced, the activity patterns of fault and sedimentation rates of strata are quantitatively analyzed, and the neotectonic activity episodes in Yongji subsection of Haizhou section of northern Zhongtiaoshan fault are established.

To enhance the filtering performance of the maximum correntropy Kalman filter(MCKF) method in complex environments, an adaptive maximum correntropy Kalman filter algorithm(AMCKF) for GNSS/SINS integrated navigation systems is proposed. Firstly, based on the relationship between the filtering fault detection function values at the current and the past (l-1) time steps and the detection threshold, two mapping relationships of 0 and 1 are formed. Then, a window of length l is constructed using the mapped values, and a kernel width adaptive adjustment algorithm is proposed. Finally, this kernel width adaptive adjustment algorithm is applied to MCKF to form the AMCKF algorithm for the integrated navigation system. Experiments are conducted on a GNSS/SINS integrated navigation system under measurement environments with Gaussian white noise and heavy-tailed impulsive noise. The results indicate that AMCKF can adaptively adjust the kernel width value according to different measurement noise environments, thereby improving the filtering accuracy of the integrated navigation system. Compared with KF and MCKF, AMCKF can improve position accuracy by approximately 26.5% and 16.4%, respectively, and improve velocity accuracy by approximately 15.5% and 6.4%, respectively.

To address the low accuracy of zenith tropospheric delay(ZTD) models and the scarcity of water vapor data in Antarctica, we use ZTD data from six global navigation satellite system(GNSS) stations in Antarctica, ECMWF reanalysis v5(ERA5) data, and radiosonde(RS) data from 2018 to 2021. First, the ZTD accuracy of UNB3m, EGNOS, and GPT3 models in Antarctica is analyzed. Then, the ZTD correction and PWV conversion models are constructed separately based on extreme gradient boosting(XGBoost). The results show that the average root mean square errors(RMSEs) of UNB3m-ZTD, EGNOS-ZTD, and GPT3-ZTD of six GNSS stations in Antarctica are 98.12 mm, 116.13 mm, and 24.31 mm, respectively. After correction using XGBoost, the average RMSEs of UNB3m-ZTD, EGNOS-ZTD, and GPT3-ZTD from 2020 to 2021 are 10.46 mm, 10.50 mm, and 10.60 mm, respectively, demonstrating higher accuracy and closeness between the models. The average RMSEs of PWV converted from the corrected UNB3m-ZTD, EGNOS-ZTD, and GPT3-ZTD using XGBoost are 1.71 mm, indicating high accuracy.

This study aims to examine the monitoring and early warning abilities of the Yunnan seismic station network using the 72 h continuous waveform recordings recorded at 2 060 stations. The evaluation index used was the maximum probability peak displacement(PGD) of background noise at each station. The findings revealed that the average monitoring capacity of the Yunnan seismic network raised to M_L1.0, while the smallest earthquake that could be monitored was M_L0.1, and the monitoring capacity was comparatively weak in the central and northwestern Yunnan area. Moreover, the average values of the minimum magnitude of earthquake early warning, the warning time after the triggering of the first station, and the warning time after the earthquake were M_L2.2, 4.0 s, and 6.1 s, respectively. Furthermore, the planning layout of the Yunnan seismic station network fulfilled the criteria for the initial establishment of earthquake early warning.

Based on the earthquakes recorded by Gansu early warning system since its operation and the output results of early warning system, a comparative study is conducted on the output magnitude of earthquake early warning system and the officially cataloged magnitude, and the distribution of magnitude errors is analyzed. We use the back-propagation neural network to learn and predict the warning magnitude parameters, and obtain the warning magnitude. The results indicate that for earthquakes with smaller actual magnitudes, the estimated magnitude is larger, while for earthquakes with larger magnitudes, the estimated magnitude is smaller. The neural network propagation algorithms can simulate and predict warning magnitude, and reduce the deviation between warning magnitude and cataloged magnitude.

High-precision polar motion prediction is crucial for applications such as real-time satellite orbit determination and deep space probes navigation. We combine the singular spectrum analysis(SSA) and weighted least squares(WLS) models, which takes into account the temporal variability of periodic components of polar motion. Combining with the auto-regressive(AR) model, we prove the effectiveness of SSA+WLS+AR model in improving the accuracy of polar motion prediction. We analyze the impact of detrending, the length of basic sequence, and the weighting method on the final prediction accuracy of the SSA+WLS+AR model. The results show that in the X direction, the model combination of "no detrending+50-year basic sequence+inverse weighting" has the highest prediction accuracy, while in the Y direction, the model combination of "detrending +50-year basic sequence+inverse weighting" has the highest prediction accuracy. When the prediction span is from 150 to 360 days, the prediction accuracy of SSA+WLS+AR model is better than that of bulletin A provided by international Earth rotation service(IERS), with maximum improvements of 33% and 26% in the X and Y directions, respectively. The prediction results show that the first-day prediction accuracy of polar motion is significantly better using the C04 20 sequence compared to the C04 14 sequence.

Taking the hilly open-pit mining area in central Shandong as the study region, this research analyzes the impacts of different DEMs(SRTM-1, SRTM-3, ALOS-DEM, ASTER-GDEM, and LiDAR-DEM) and their elevation accuracy/spatial resolution on SBAS-InSAR deformation monitoring performance and geometric distortion identification. Results demonstrate that compared to spatial resolution, DEM elevation accuracy plays a more critical role in deformation monitoring and significantly affects measurement precision. Both DEM elevation accuracy and spatial resolution substantially influence the identification of shadow and layover areas. These findings provide guidance for DEM data selection in subsequent time-series deformation monitoring in complex terrains.

To investigate the response of L-band ionospheric scintillation to equatorial anomaly characteristics in low-latitude regions, this study utilizes L-band scintillation observation data from three Australian stations(Darwin, Weipa, and Willis Island) combined with global ionospheric VTEC data provided by the Chinese Academy of Sciences(CAS).The study examines the relationship between ionospheric scintillation and VTEC equatorial anomalies under geomagnetically quiet conditions. Results show a significant positive correlation between ionospheric scintillation and equatorial anomaly characteristics at the three stations. On scintillation days, the ionospheric VTEC peak-to-valley difference, peak-to-valley ratio increase, and gradient changes are more pronounced. This paper reveals the response mechanism and investigates the correlation between VTEC and its gradients with scintillation, which is significant for the rapid identification and judgment of scintillation phenomena and for GNSS engineering applications.

The linear or nonlin drift of the spring gravimeter must be addressed for the existing observation system based on spring gravimeters to monitor the long-term change signal of gravity. Simple linear fitting is usually difficult to simulate the real drift of the instrument over a long period of time, and too high-order fitting will also remove the trend change signal of the signal. This study introduces linear and nonlinear drift correction models to more reasonably remove the drift. This study uses the data of the gPhone gravimeter at Zigui station in 2017 and the gPhone gravimeter at Wushi station in 2023 for analysis and verification. First, the correlation between each channel of Zigui station and the original gravity channel is analyzed, and the theoretical gravity effect of the Three Gorges water storage on the Zigui station is calculated with the results that reach more than 100 μGal. Then, the model coefficients are obtained using a variety of regression analysis methods, and the residual results are studied after deducting various correction values and drift terms. The research results show that the changes in the internal pressure and temperature of the instrument are the main causes of gravity data drift. In the regression model used in this paper, the nonlinear regression model(pure quadratic regression) drift removal results can better reflect the gravity changes caused by water storage, and the residual effect obtained after smoothing is closer to theory than the conventional polynomial fitting method for drift removal. Similar conclusions were obtained by verifying the data from Wushi station.

Based on nearly one year of GNSS-R data from the GNSS occultation sounder Ⅱ(GNOS-Ⅱ) onboard the Fengyun-3E(FY-3E) satellite, this study conducted global soil moisture inversion modeling and evaluated the inversion results from different satellite systems and their combined observations. The results indicate that there are systematic biases in the reflectivity distributions calibrated by the reflected signals of BDS, GPS, and Galileo. However, the inversion results based on different systems have similar accuracy. The predicted soil moisture values show good consistency with the level 3 soil moisture products provided by the SMAP satellite, with a correlation coefficient of 0.855 and an unbiased root mean square error of 0.063 cm³/cm³. When combining different systems for inversion, the cumulative distribution function matching method was used to recalibrate the effective reflectivity of each satellite system's observations, which further improved the accuracy of surface soil moisture inversion.

Existing research on GNSS signal classification primarily targets professional-grade receivers, distinguishing between line-of-sight(LOS) and non-line-of-sight(NLOS) signals through the extraction of signal features to achieve high-accuracy positioning. However, the signal features and classification methods used in these studies may not be applicable to the signal characteristics of low-cost GNSS chips in smartphones. This paper proposes a machine learning-based method for classifying smartphone GNSS reception signals into LOS and NLOS. The method combines five key indicators: carrier-to-noise ratio, elevation angle, pseudorange residuals, normalized pseudorange residuals, and pseudorange residual percentage. It also integrates deep learning-based zenith view semantic segmentation and satellite calibration techniques to construct an accurate training dataset. Evaluations of various machine learning models in typical urban scenarios show that the proposed method achieves an average classification accuracy of 85.8% across different smartphone models.

The variational mode decomposition(VMD) exhibits superior performance, and the setting of K and alpha parameters significantly influences its decomposition result. We optimize the selection of these two parameters based on sparse index, enabling the adaptive determination of the optimal K and alpha values. On this basic, VMD method is applied to seismic signal data observed by four types of second-sampling instruments at Yichang station, including BBVS-60 seismometers, DZW gravimeters, VP-type tiltmeters, and water level gauges, and time-frequency analysis is conducted combining with Hilbert transform. The results show that the optimal K and alpha values differ for each of four instruments. The K value represents the type of coseismic signal frequencies that can be decomposed, suggesting that the four instruments respond differently to the same seismic signal.

The accuracy of gravity matching navigation is influenced by the adaptability of the sailing sea area. To ensure the effectiveness of matching, it is crucial to conduct path planning for the submersible. In response to the issues of low efficiency, susceptibility to local optimal solutions, and unstable performance of existing algorithms, this paper proposes a hybrid algorithm-particle swarm optimization and grey wolf optimization(PSO-GWO) to enhance the path planning efficiency of submersibles. Building on the traditional grey wolf optimizer(GWO), the proposed algorithm incorporates the memory mechanism of the best position information of particle movement from particle swarm optimization(PSO), reconstructing the update functions for velocity and position, thereby improving the optimization capability and convergence speed of the GWO algorithm. Experiments were conducted using PSO-GWO, GWO, and PSO algorithms on a two-dimensional grid map discretized based on adaptability. The results show that compared with the GWO and PSO algorithms, the PSO-GWO algorithm reduces the planned path length by 10.99% and the number of iterations by 82.43%. This algorithm reduces redundant travel and accelerates convergence, significantly improving the underwater navigation efficiency of the submersible.

This paper utilizes the ERA5 multi-element dataset to predict ERA5 water vapor by integrating the fast Fourier transform(FFT) and convolutional long short-term memory(ConvLSTM) methods. Firstly, the common periods of various meteorological elements are extracted using FFT. Subsequently, multiple meteorological elements with different common periods and individual water vapor data are selected as model inputs, and the ConvLSTM method is employed to train the ERA5 water vapor and construct the prediction model. Finally, the prediction performance of the model for point and spatial water vapor is evaluated using GNSS water vapor and actual ERA5 water vapor. The results indicate that the ERA5 water vapor prediction method based on FFT and ConvLSTM can effectively predict water vapor for the next 120 hours, with high accuracy in both single-point and spatial areas, providing a data foundation for short-term precipitation warnings.

With the widespread use of GNSS on civil aviation and UAV platforms, scenarios with large elevation differences are increasingly emerging, which puts higher demands on the accuracy of vertical corrections for tropospheric delays. As the most advanced ZTD model currently available, GPT3 has limitations in its vertical corrections for temperature and pressure, making it only suitable for near-surface applications. To address this issue, this paper proposes an improved method of GPT3 by integrating a global temperature lapse rate grid model and a multi-variable atmospheric pressure-altitude formula, constructing the IGPT3 model, and evaluating its adaptability. The results show that compared with UNB3 and GPT3, IGPT3 has improved accuracy by 25.0%, 18.2%, 16.1%, and 72.2%, 50.0%, 69.9% in predicting temperature lapse rate, temperature profile, and pressure profile, respectively. Moreover, the precision improvements in predicting ZHD and ZTD profiles using IGPT3 reached 29.3 mm and 29.0 mm, respectively. Furthermore, the precision of GNSS water vapor inversion at most IGS stations was improved with the use of IGPT3, with the maximum improvement reaching 3.07 mm.

To address the limitations of traditional RAIM algorithms, including abnormal fault detection and insensitivity to small faults, we introduce the concept of variance inflation from robust estimation into receiver autonomous integrity monitoring(RAIM). A RAIM algorithm combing variance inflation model is proposed, with an improved fault handling process. Integrity determination is performed using the user's protection level based on positioning uncertainty, and multi-constellation simulations and real-world tests in complex environments are conducted. The simulation results show that the proposed method can accurately detect a significant fault of 30 meters and effectively mitigate the impact of a small 5-meter fault on positioning results, successfully restoring the positioning error level to the state before the fault is introduced. The real-world test results show that the proposed method achieves horizontal and vertical availability rates of 95.38% and 98.74%, respectively, which are 11.63% and 5.06% higher than traditional RAIM algorithms. In terms of positioning accuracy, compared to traditional RAIM algorithms, the proposed method improves precision in E, N, U directions by 23.03%, 11.68%, and 26.79%, respectively.

This paper introduces the data preprocessing and interpolation methods for universal time(UT1) and analyzes the factors affecting the interpolation accuracy of UT1, including different interpolation methods and differences in data preprocessing. The study combines international products with domestic co-observation data to analyze the interpolation accuracy of UT1 under different observation frequencies of very long baseline interferometry(VLBI). The results show that among different interpolation methods, cubic spline interpolation is superior. The interpolation process of UT1 must consider the influence of Earth's solid tides, while high-frequency corrections can be neglected. Compared with daily observations, when the observation interval is less than 2 days, the deviation of UT1 can be stabilized at around 0.05 ms. Increasing the observation interval further will lead to a more pronounced increase of UT1 deviation. Verification using domestic observational data shows that with an observation interval of 2 days, the accuracy of UT1 can reach around 0.05 ms.

The BDS-3 and Galileo both provide five-frequency signal services. To fully utilize the multi-frequency signal data, a BDS-3/Galileo multi-frequency single point positioning (SPP) model based on the ionosphere-free combination is established, and the multi-frequency ionosphere-free combination coefficients are determined. Data from 48 multi-GNSS experiment (MGEX) stations are selected to systematically evaluate the performance of multi-frequency pseudorange SPP based on the ionosphere-free combination. The experimental results show that multi-frequency combined observations help to improve the SPP positioning accuracy of the BDS-3, Galileo, and BDS-3/Galileo systems. Compared with three-frequency SPP positioning, the positioning accuracy of four-frequency and five-frequency SPP has been improved to varying degrees. The improvement is most significant for the BDS-3 system. For the BDS-3 three-frequency SPP positioning, the RMS mean values in the E, N, U directions are 0.56 m, 0.59 m, 1.46 m, respectively, while the RMS mean values for four-frequency and five-frequency positioning are similar, at 0.53 m, 0.55 m, 1.40 m and 0.52 m, 0.55 m, 1.38 m, respectively. Compared with the single BDS-3 and Galileo systems, the five-frequency SPP positioning accuracy of the BDS-3/Galileo combined system has increased by 30.8%, 29.1%, 25.4% and 28.0%, 30.4%, 25.9%, respectively.

To further evaluate the technical performance of domestic independently developed absolute gravimeters, this study conducted comparison observations using multiple absolute gravimeters in the cave of the Huazhong University of Science and Technology National Gravimetry Laboratory. Through unified data processing, high-precision absolute gravity comparison data were obtained. The results demonstrate that no significant deviation exists between atomic interferometry absolute gravimeters and laser interferometry absolute gravimeters in this comparison, with deviations all within -4.95 μGal to 5.31 μGal. Each atomic interferometry absolute gravimeter achieved an observation precision of 1 μGal during continuous 4-hour measurements, with inter-instrument deviations maintained below 10 μGal, demonstrating excellent stability and consistency. This study marks the first comparison measurements conducted on multiple domestically developed absolute gravimeters featuring independent domestic. It involved detailed data processing, scientific evaluation, and a multidimensional performance assessment, providing crucial references for the subsequent development and application of domestic gravimeters.

We quantitatively analyzed the crustal strain changes in Xuzhou and Gaochun areas of Jiangsu province from 2019 to 2023 using four-component borehole strainmeters, and explored the characteristics of regional strain field and its relationship with seismic activity. According to the strain parameter results, both Xuzhou and Gaochun areas were in a stable state during the study period. The response values of tidal factors at Gaochun seismic station exhibited an abnormal change of first dispersion, then stabilization before and after the M5.0 earthquake in Dafeng sea area of Yancheng, Jiangsu province. Through the analysis of its variation characteristics, the relationship with the strike of faults and the focal mechanism solution of earthquakes, it can be inferred that in the process of earthquake preparation, the stress and strain in this area experienced a process from accumulation to release, and the tidal factors can reflect this change to a certain extent.

In order to improve the medium and long term prediction accuracy of polar motion, the LS+Informer(least-squares extrapolation and Informer, LS+Informer) prediction model is proposed based on the traditional LS+AR prediction model combined with deep learning method. The mean absolute error(MAE) was used as the evaluation index based on LS+AR forecast model and Bulletin A forecast results. After LS+Informer method is adopted, the medium and long term prediction accuracy of PM_X and PM_Y components of polar motion can be significantly improved, and the amplitude can reach 61.94% and 64.86% respectively. At the same time, the MAE value can be controlled within 10 mas in the medium and long term 365-day phase. The results show that the prediction accuracy of LS+Informer model is better than that of LS+AR model, and better than that of Bulletin A. The results demonstrate that the LS+Informer model can be effectively used in medium and long term polar motion prediction.

We investigate the deviation between IGRF13 model data and unmanned aerial vehicle(UAV) geomagnetic data in localized regions of China. By analyzing the differences in total geomagnetic field intensity, as well as the northward, eastward, vertical, and horizontal components of geomagnetic field between IGRF13 model data and aeromagnetic data in Weishui in Shaanxi province and Yuyao in Zhejiang province. The results show that the difference in total geomagnetic field intensity between IGRF13 model data and geomagnetic data in localized regions of China ranges from 100 to 200 nT. In the northwestern region of China, the difference is approximately 100 nT, while in the eastern coastal region, it is around 200 nT. After systematic calibration, the mean absolute error between the two datasets is less than 50 nT.

To simulate the impact of terrain on co-seismic deformation, this paper established three different terrain models. The results show that compared with flat terrain, convex terrain reduces the amount of horizontal displacement, while concave terrain significantly increases the amount of horizontal displacement. The terrain difference in the epicentral area of the 2024 Wushi, Xinjiang M_W7.0 earthquake is significant, and the impact of the real terrain on the co-seismic deformation of this earthquake is not yet clear. This paper uses the spectral element method to simulate the co-seismic deformation of the Wushi earthquake and compares it with the co-seismic displacement field of D-InSAR. The results indicate that the impact of terrain factors on co-seismic deformation can reach 8.5%, 26.9%, and 6.8% in the E, N, and U directions, respectively.

We conduct a detailed analysis of the spatial configuration of Beidou-3 constellation, and construct a dynamic link constraint model from two aspects: satellite visibility and antenna directivity. We obtain the real satellite orbit parameters through two line elements (TLE) file, construct the Beidou-3 constellation based on STK, and comprehensively analyze the topology characteristics of Beidou inter-satellite link. The simulation results have important guiding significance for further completing the link budget, achieving autonomous orbit determination and time synchronization between satellites.

Based on the structural characteristics of the Xianshuihe fault zone, this study divides the five sections of Luhuo, Daofu, Qianning, Zheduotang, and Kangding-Moxi, and quantitatively reveals the horizontal slip rate and kinematic characteristics of each section through multi-source observation data of cross-fault leveling, baseline/ranging, and horizontal creep. The results show that the whole Xianshuihe fault zone is dominated by left-lateral strike-slip mode from 1982 to 2024. The strike-slip rates of Juwo and Xialatuo in Luhuo section are -0.9 mm/a and -2.86 mm/a, and the cumulative strike-slip displacements are 40 mm and 130 mm, which are significantly higher than the activity intensity of Gelu and Xuxu stations. The strike-slip rates of Goupu and Goupu creep stations in Daofu-Qianning section are -0.97 mm/a and -0.58 mm/a, and the cumulative displacement shows a linear growth trend. The horizontal displacement of Longdengba and Laoganning stations is small, and the local fault zone is weakly sinistral. The Zheduotang observation site in the Kangding-Moxi section shows a +0.2 mm/a dextral strike-slip, while the Yulin observation site maintains a stable left-lateral strike-slip of -0.12 mm/a, and its deformation has significant seasonal fluctuations (amplitude of about 1.5 mm to 2.3 mm). The cross-fault leveling of the Anshun site shows continuous tensile normal fault activity, and the linearity of the movement trend reaches 0.933 and 0.824, respectively.The results of segmented comparison show that the activity intensity of the northwestern section is significantly higher than that of the southeastern section, and the vertical movement shows that the thrust of the northern section and the normal fault activity of the southern section are structural inversion. The segmentation difference is related to the fault geometry and the physical properties of the medium. The medium strength of the conversion layer in the northwest section may be lower than that in the southeast section, which is easy to trigger slip and lead to shorter earthquake recurrence period. Combined with the regional stress field, it is found that the locking degree of the Xianshuihe fault zone has changed in different periods, showing that the fault in the northwest section is more active than that in the southeast section, and the locking is weak. At the same time, after the Wenchuan M_S8.0 earthquake, the Lushan M_S7.0 earthquake, and the Luding M_S6.9 earthquake, the extrusion rate of the Bayan Har block to the Sichuan basin accelerated, which affected the far-field left-lateral strike-slip rate of the Xianshuihe fault and the accumulation rate of fault slip deficit, which in turn led to the difference in the stress and strain accumulation rate of each segment on the Xianshuihe fault zone.

Based on the statistical analysis, correlation fitting and preprocessing of high-precision continuous observation data of four trace hydrogen observation points in fault zones of northwestern Yunnan over the past five years, we evaluate the seismic prediction efficiency of observational data, and analyze the characteristics and causes of trace hydrogen concentration anomalies related to earthquakes combining with previous studies. The results show that: 1) The concentration variations of hydrogen escaping from hot springs in northwestern Yunnan are correlated with temperature and air pressure, showing distinct annual variation features. In contrast, hydrogen escaping from soil is essentially uncorrelated with meteorological elements. Comparison with previous studies, there is a significant spatial heterogeneity in the distribution of trace hydrogen concentration in fault zones, which is not controlled by a single factor. 2) All of four trace hydrogen observation points in northwestern Yunnan are effective seismic prediction indicators with statistical significance. The short-term prediction effect of hydrogen escaping from soil is better but with relatively lower credibility. The prediction efficiency of hydrogen escaping from hot springs is mainly in medium to long term, with relatively higher credibility. 3) There is a close correlation between hydrogen anomalies in fault zones and seismic activities in northwestern Yunnan. Seismic precursory anomalies typically manifest as sudden increases or sawtooth fluctuations. Due to differences in hydrogen sources, escaping processes, and geothermal storage temperatures in different regions, the geochemical background values of hydrogen escaping from hot springs and soil also exhibit significant spatial heterogeneity.

At present, the common detection method of integrated navigation system soft faults is to combine the sequential probability ratio test (SPRT) algorithm with the residual Chi-square detection algorithm. However, this algorithm has the defects of low detection accuracy and inability to detect multiple consecutive soft faults. Aiming at this problem, this paper first proposes an improved SPRT detection algorithm based on fading factor to reduce the influence of historical information on fault detection statistics and enhance the effect of current information on fault detection statistics. Then, the fault check statistic of the improved SPRT detection algorithm is designed, and combined with the residual Chi-square detection algorithm, an integrated navigation soft fault detection algorithm is proposed. Finally, based on GNSS/SINS integrated navigation system, this article has carried on the integrated navigation system soft failure detection simulation experiment.The experimental results show that compared with the classical algorithm, residual Chi-square detection algorithm, the improved algorithm not only has high precision and can accurately detect multiple consecutive soft faults, which can guarantee the stability of the integrated navigation system.

To address the issue of deviations in amplitude extraction caused by unmodeled errors in global navigation satellite system interferometric reflectometry(GNSS-IR) soil moisture inversion, this study proposes a method that utilizes a semi-parametric model to introduce nonparametric vectors compensating for unmodeled errors, thereby optimizing amplitude extraction. The soil moisture inversion results based on parametric models are compared with those derived from semi-parametric models. The findings demonstrate that the amplitude extracted by the semi-parametric model achieves higher accuracy in both single satellite and multi-satellite fusion scenarios. The proposed approach effectively improves inversion precision by mitigating unmodeled errors through semi-parametric compensation.

We quantify surface water storage anomalies using GRACE satellite Mascon data and hydrological model data combining with water level and area data, estimate groundwater storage anomalies in Dongting Lake basin based on water balance equation, analyze the spatiotemporal variation characteristics and influencing factors of groundwater storage anomalies. The results show that after incorporating changes in surface water storage, the correlation between the inverted groundwater storage anomalies at the lake scale and the observed groundwater data improved from 0.40 to 0.65, reaching 0.75 in areas with dense groundwater wells. The overall groundwater storage anomalies in Dongting Lake basin show a downward trend, with a loss rate of-5.05 mm/a. Spatially, there is a significant difference between the northern and southern areas. Precipitation influences groundwater storage anomalies through its impact on surface water, with some lag due to hydrological processes, while human activities have a limited effect. This study reduces uncertainties generated in separating surface water storage, providing data support for groundwater dynamic research and water resource management in Dongting Lake basin.

This article utilizes observational data from seven geoelectric field stations in the Shandong region starting in 2021. It determines the dominant azimuth angle α of the geoelectric field using a geoelectric rock mass fracture model. The jumping range Δα did not meet the criteria for judgment and did not meet the abnormal indicators. According to the prediction rules of this method, it is analyzed that the probability of a moderate to strong earthquake occurring in Shandong region in the near future is not high. Based on the analysis of the development of rock fractures in the site reflected by the advantageous azimuth results, the results show that the rock fractures in Heze station located on the east side of the Liaokao fault zone and Zoucheng station located between the Cangshan-Nishan fault zone and Fushan fault zone are in the generation stage, which is a common background for the development of small and medium-sized earthquakes area. The rock fractures of Anqiu station and Lingyang station located in the northern section of the Yishu fault zone and Rushan station on the east side of the Muping-Jimo fault zone are in the stage of development or growth, which is in line with the background of nurturing moderate to strong earthquakes and deserves special attention.

This study focuses on the classification problem of mining seismic and blasting signals in a mine in Gansu province. Common unsupervised classification methods such as support vector machine, K-means clustering, and principal component analysis were analyzed. These methods face significant challenges in terms of insufficient feature selection, low classification accuracy, and imbalanced samples. To attempt to address these issues, this paper employs a lightweight collaborative learning method(LCL-SSS) that combines MiniRocket feature extraction with improved K-means clustering, aiming to enhance the accuracy and efficiency of classification. Through time-frequency analysis, it was found that the initial P-wave frequency of blasting events is mainly concentrated between 80 to 200 Hz, while the P-wave frequency of mining seismic events is distributed between 20 to 120 Hz. After 30 training experiments, the classification accuracy of the LCL-SSS method reached 95.07%, effectively capturing key features in mining seismic waveforms.