Taking into account the low temporal-spatial resolution of the existing ZTD and ZWD vertical profile model, we analyze the temporal-spatial distribution characteristics of ZTD and ZWD height scale factors in China based on the 2014-2016 meteorological reanalysis data MERRA-2 provided by NASA. The results show that both ZTD and ZWD height scale factors have obvious annual and semi-annual changes, which are significantly correlated with longitude and latitude, and the temporal-spatial distribution characteristics of ZTD and ZWD height scale factors are significantly different.

This paper takes Hebei province as the research area, using wavelet transform and RBF neural network methods to carry out GNSS-PWV prediction research. Firstly, wavelet decomposition is performed on the PWV sequence of GNSS stations, and then the high and low frequency signals decomposed by the wavelet are predicted by the RBF neural network. Finally, the appropriate high frequency and low frequency signals are selected through experiments to reconstruct the GNSS-PWV prediction values. Compared with the actual measured GNSS-PWV values and RBF predicted PWV values, we find that the accuracy of GNSS-PWV predicted based on wavelet transform and RBF neural network is higher than that of the RBF neural network, and the accuracy of the prediction results decreases with the increase of the prediction time.

Based on continuous GNSS data from crustal movement observation network of China (CMONOC), we select the coordinate time series of 25 stations in Yunnan province to study the influence of mass loading on noise model. After calculating the displacements induced by continental water storage, non-tidal atmospheric and non-tidal oceanic loading, we analyze the different combinations of noise models and ascertain trend uncertainties using maximum likelihood estimation. Then, we establish the best noise model before and after environmental loading correction of all GNSS stations, and estimate the velocity uncertainty. We find that nearly all the coordinate components are characterized by flicker noise plus white noise(FN+WN), the best noise model can be changed by environmental loading correction, and the velocity uncertainty of 72%,80%,68% stations can be decreased with environmental loading correction for E,N,U direction, respectively.

Considering that the traditional harmonic model has difficulty accurately describing the nonlinear variation of GNSS coordinate time series, the signal and noise cannot be separated well, which further affects the gross error detection and noise estimation. This paper proposes an algorithm for gross error detection and noise component estimation based on singular spectrum analysis(SSA). The basic idea of the proposed algorithm is to separate the signal and noise with the SSA firstly, and then detect gross error in noise based on the inter-quartile range (IQR) criterion. Finally, we employ the least squares variance component estimation (LS_VCE) to quantitatively estimate each noise component. The analysis results show that the success rate of gross error detection of the new algorithm is higher than that of the traditional algorithm and the noise component estimation derived by the new algorithm is closer to the true value compared with the traditional algorithm.

We propose a BDS-3 ultra-rapid clock offset prediction algorithm based on EM algorithm optimized relevance vector machine. First, we use the combined MAD method to preprocess the clock data and perform one time difference. Then, we use the one time difference data to train the RVM model, we use the EM algorithm to iteratively obtain the hyperparameters of the model, and finally we use the optimized RVM model to predict. We then restore the one-time difference prediction value of the clock offset to obtain the prediction value of the clock offset. The prediction test is carried out with the measured BDS-3 ultra-rapid clock offset data provided by iGMAS, and the prediction results of this method are compared with the QP model, the SA model and the ultra-rapid clock offset prediction product (ISU-P) of iGMAS. The results show that the mean accuracy of the BDS-3 satellite clock offset data prediction by the RVM model is better than 0.61 ns regardless of whether the forecast is 6 h, 12 h or 24 h. Compared with ISU-P, QP model, SA model, the prediction accuracy of the 24 h BDS-3 satellite clock offset has been improved by 64.1%, 50.0%, 49.2%,respectively.

Based on the measured data of MGEX stations, we use the cross validation method between systems to check the quality of Beidou/GNSS precise point positioning (PPP). We analyze the accuracy and convergence speed performance of multi-GNSS PPP with different combinations. The results show that compared with single BDS, multi-GNSS can accelerate the convergence speed as well as the accuracy of PPP. The greater the system combinations number, the higher the positioning accuracy and the faster the convergence speed of PPP. Then, we use the cross validation method between systems to check the accuracy and reliability of PPP results in static, pseudo-dynamic and marine dynamic positioning modes.

This paper analyzes the ARAIM performance of GNSS dual constellations, three constellations and four constellations combination when only considering satellite failure and considering satellite failure and constellation failure at the same time. It analyzes the ARAIM performance of ground stations under LPV-200 through measured data, and further simulates the availability of GNSS ARAIM under LPV-200 in the world. The results of measurement and simulation show that the availability of ARAIM decreases from the equator to the poles in a symmetrical distribution. As a heterogeneous constellation, BDS can significantly increase the availability of ARAIM in the Asia Pacific region. Compared with the dual satellites failure, the availability of GPS+BDS ARAIM decreases greatly when the single satellite and single constellation failures occur simultaneously. The availability of ARAIM of GPS+GLONASS+BDS and GPS+GLONASS+BDS+Galileo decreases slightly.

In order to analyze the accuracy of the earth rotation parameters solved by VLBI observation data, according to VLBI theory and error equation, we calculate the parameters using the VLBI data in 2020 and the XA and XB frequency channel data from continuous intensive CONT17 observation. We use the EOP14 C04 sequence as reference to obtain the external coincidence accuracy. The results show that the external coincidence accuracy of each component of rotation parameters can meet the requirements of high accuracy through the VLBI data. Compared with the continuous GPS data which are in the same period, the VLBI data present similar accuracy in calculating earth rotation parameters. The XA and XB frequency channel data perform similar accuracy in dealing with polar motion series, but the former performs better in stability and has great advantages in UT1-UTC sequence.

In this paper, we correct the deviation in the residual and derive the almost unbiased formula for calculating the unit weight variance for Liu-type estimator based on the quadratic mathematical expectation formula. The analysis results of two examples show that the unit weight variance computed by the formula of this paper is closer to the true value than that by traditional formula, which is based on the biased residual.

In order to investigate whether there is triggering relationship between the 2017-08-09 Jinghe M_S6.6 earthquake and the 2018-10-16 Jinghe M_S5.4 earthquake in Jinghe County, based on the Jinghe  M_S6.6 earthquake co-seismic fracture dislocation model and regional crustal velocity structure, we use a viscoelastic model to calculate the surface displacements, co-seismic and post-seismic stress field disturbance of the 2017 Jinghe M_S6.6 earthquake. We analyze the stress triggering relationship between the M_S6.6 and the M_S5.4 earthquake. The results show that the co-seismic displacements caused by the Jinghe M_S6.6 earthquake are mainly surface vertical displacements, with a maximum of 84 mm. The horizontal maximum displacement is 25 mm. The earthquake causes the increase of Coulomb stress in the seismogenic fault and its intersection with Bolokenu-Aqikekuduke fault, the eastern segment and branch of Koxemqed fault, and the eastern segment of Kashgar river fault. The Coulomb stress in these areas near the epicenter of Jinghe M_S6.6 earthquake increases by more than 10 kPa, but the disturbance is basic elastic stress response in 5~10 a scale, without significant changes with time. The variation of co-seismic Coulomb stress in the epicenter of Jinghe M_S5.4 earthquake caused by the Jinghe M_S6.6 earthquake is significantly lower than the trigger threshold of 10 kPa. The analysis shows that there is no co-seismic or post-seismic stress trigger relationship between the two earthquakes.

We use the double difference location method to relocate the 15 816 earthquakes recorded by dense station array in northwest Yunnan from April 2018 to September 2020. 14 110 relocation events are obtained. We obtain the accurate spatial distribution of earthquakes in northwest Yunnan. The results show that: 1) The distribution of earthquakes in the study area is not uniform. Most of the earthquakes are distributed along the boundary of the deep and large faults, which fully shows the pattern of faults; 2) The predominant focal depth of the earthquakes is 7-11 km, indicating that the earthquakes mostly occur in the middle and upper crust; 3) The depth distribution characteristics of the earthquakes in each profile show the structural characteristics of the fault in the deep.

Using the magnetotelluric sounding method, we explore the 3D seismic deep structural characteristics in Shanxi reservoir area for the first time and obtain the 3D electrical structure of 70 km². Then we establish the 3D geological structure model in this area and discuss the deep structural environment of reservoir-induced earthquakes. The results show: 1) In Shanxi reservoir area, there is a triangular fault block trending to south-west which is mainly composed of three faults, the Shuangxi-Jiaoxiyang faults is the principal of the three faults, and almost all earthquakes with magnitude greater than 2.5 basically occurred in this special structure area. 2) There are three main low-resistance channels in the deep part. Seismic activity is concentrated along the middle f_11-3 low-resistance channel. With groundwater permeating from southeast to northwest along the f_11-3 fluid channel, seismic activity also migrates periodically along this direction. 3) Wenzhou-Taishun fault and granite in the east block the eastward development of Shuangxi-Jiaoxiyang fault, resulting in the inability of in-situ stress to propagate eastward, which may be the main reason for the absence of earthquakes to the east of the fault.

In this study, we add the cumulative absolute velocity (CAV₅) to the existing seismic liquefaction-induced lateral spread database to consider the effect of focal mechanism on liquefaction-induced lateral spread. Then, we use the radial basis function neural network (RBFNN) method to establish the liquefaction-induced lateral spread  prediction model of earthquake liquefaction. The results show that our model has higher prediction accuracy than other models; CAV₅ can replace the magnitude and epicentral distance in the prediction of liquefaction-induced lateral spread. The magnitude, epicentral distance and liquefiable soil layer thickness of all parameters are more sensitive and have a greater impact on liquefaction-induced lateral spread.

To study the feasibility of interferometric point target analysis (IPTA) method in giant landslide monitoring, we use IPTA method to obtain the overall deformation trend and time series deformation of the Daguangbao landslide with 65 Sentinel-1A images. The global precipitation measurement data are used to analyze the relationship between deformation and precipitation, and we verify the deformation results by the StaMPS-SBAS method. The results show that the landslide is in a state of deformation during the observation period, and the deformation rate along the radar line-of-sight (LOS) direction is up to -50.590 mm/a. The deformation velocity of the feature points increases significantly during rainy season, and there is a risk of landslide development again. This study demonstrates that IPTA method shows good application effect in giant landslide deformation monitoring.

This study proposes a new method for predicting surface deformation caused during GERD storage based on spherical harmonic transform. Firstly, it is assumed that the GERD reservoir is filled up during 5, 10 and 15 years respectively, and the area, volume and water level of the reservoir are obtained for each month of the storage process using SRTM-DEM data. The surface deformation caused by the corresponding storage process is calculated after spherical harmonic expansion and the accuracy of the results is increased by increasing the upper limit of the maximum harmonic degree. The estimated vertical displacement velocity induced for each of the three filling strategies are 11.8 mm/a, 5.9 mm/a and 3.9 mm/a, respectively. The induced east-west displacement velocity are 1.8 mm/a and 1.4 mm/a, 0.9 mm/a and 0.7 mm/a, 0.6 mm/a and 0.4 mm/a, respectively. The induced south-north displacement velocity are 2.6 mm/a and 4.4 mm/a, 1.3 mm/a and 2.2 mm/a, 0.8 mm/a and 1.5 mm/a, respectively.

Based on GPS data from 2009 to 2017 and Sentinel-1 SAR images including ascending and descending data acquired from 2017 to 2019, we use SBAS-InSAR to inverse the current surface deformation rate field of the northern margin fault of Yangyuan basin. According to the statistics of the vertical sliding rate of the designated interval points on the cross fault section line, the vertical sliding rate with two sides of the east, middle and west sections of the fault in the northern margin of Yangyuan basin are about 1.04 mm/a, 1.43 mm/a and 0.72 mm/a, respectively. The left lateral strike slip movement characteristics of Yousuobao-Songzhikou fault and the intersecting relationship between the fault and the middle segment of the fault in the northern margin of Yangyuan basin are the main reasons for the higher fault activity level in the middle segment of the fault in the northern margin of Yangyuan basin than in the eastern segment, while the activity of the western segment of the fault in the northern margin of Yangyuan basin is not obvious. GPS data show that the fault in the northern margin of Yangyuan basin is characterized by dextral strike slip movement in horizontal direction.

We collect and sort the data of 10 phases of mobile gravity re-measurement from 2016 to 2020 in Hainan. We use the primary term scale coefficient calibrated by gravimeters sharing institutions to adjust the re-measured data of each period. The results show that the gravity field of Hainan has changed significantly during the period 2016-09~2017-05, 2017-05~10, 2018-05~10. Based on the primary term scale coefficient of the instrument in the first period of 2016, we use the gravity differential method to correct the primary term scale coefficient. We then reprocess the quasi-stable adjustment. The results show that since 2016, the differential gravity field of Hainan has changed relatively smoothly, and the change of the gravity field is basically within 30 μGal. The significant gravity field anomalies of Hainan disappear. So, if we use the gravity differential method to correct the primary term scale coefficient, we can effectively reduce the gravity field change error caused by the primary term scale coefficient error.

Based on the principal component analysis (PCA), we construct a theoretical model for three-component seismic polarization analysis and obtain more accurate horizontal azimuth and vertical inclination of the geophone. And then the seismic response is rotated to correct the direction of the geophone.We apply this method to the elastic wave velocity test between cross-well, through the polarization analysis of the measured data, the first break of P-wave and S-wave are respectively strengthened in H_P-component and R-component. This is not only conducive to the pick-up of the first break, but also can obtain more accurate wave velocity data, providing more accurate dynamic parameters for geotechnical engineering design.

In order to obtain the dynamic response of the structure, GNSS and accelerometer are combined to monitor the vibration. We propose a hybrid filter based on empirical mode decomposition(EMD) and Chebyshev filter. We filter the data collected by GNSS to identify the high-frequency and low-frequency dynamic displacements of the structure. The high-frequency dynamic displacements are integrated with the acceleration data to reconstruct the overall dynamic displacements. Through a series of simulation data, we verify the feasibility of the reconstruction displacement algorithm.

By calculating power spectrum density (PSD) and probability density function (PDF) of continuous waveform data from cave observation from Inner Mongolia seismic network from December 2019 to November 2020, we analyze background noise characteristics of the stations.The results show that background noise in the high frequency band is significantly different between day and night, the noise level during the COVID-19 pandemic is significantly lower than other times.The background noise in the secondary microseismic frequency band has a significant seasonal variation, the noise level is stronger in winter than in summer, the peak value of PSD decreases with the increase of distance from stations to the coastline. The background noise in the main microseismic frequency band has a peak in 10-20 s, the peak value is highest in winter, with no difference in spring, summer and autumn, and the difference of peak values in the same season is small at different stations.The noise level in the long period has little difference between the four seasons. Spring and summer are slightly higher than  autumn and winter.