Mass changes derived from gravity recovery and climate experiment(GRACE) data in high mountain Asia(HMA) and adjoining areas can be used to investigate the effects of regional climate factors such as the Indian monsoon, westerlies and El Nio-Southern Oscillation(ENSO). However, one recent study had a different viewpoint for the role of the westerlies in HMA than traditional studies. Thus, we turn to improved estimates of mass changes, derived the GRACE Release 06 Mascon solution from January 2003 to June 2017, and perform a novel complex empirical orthogonal function(CEOF) analysis. We find that the contributions to the mass changes in our study area, corresponding to the top three principal components, are 53%, 27% and 6%, and their correlation coefficients with Indian monsoon, westerlies and ENSO index data are as large as 0.92±0.16, 0.70±0.15, and 0.42±0.15, respectively. This suggests that the Indian monsoon, westerlies and ENSO could account for 53%, 27% and 6%, respectively, of the mass changes in the study area during the observation time span of 14 years. Considering our whole study area, the effect of westerlies is the second important one for mass changes, which supports most previous studies. We also find that ENSO exerts its effects on mass changes in specific areas(e.g., Pamir mountains, Himalayas and northwest India) through the linked Indian monsoon. Northwest India, the Himalayas and southeast Tibet are found to show a declining trend of mass changes, caused by the weakening Indian monsoon and the related ENSO, and the strengthening westerlies. The Hindu Kush, and the west and east Kunlun mountains are found to show an ascending trend of mass changes mainly due to stronger westerlies. Although influenced by the stronger westerlies, the Pamir mountains and the Tienshan show a declining trend of mass changes, since they are also affected by the weakening Indian monsoon and ENSO together with increasing air temperature trends.

We use GRACE time-variable gravity field data, provided by CSR, to invert mass change of the Antarctic ice sheet from 2003 to 2016. The results show that there is a trend of ice sheet melting in the Antarctic region, with the rate of (-101.27±7.02) Gt/a. It is continuously accelerating. Ice sheet mass accumulation appears in the EA region, with the rate of (69.09±2.64) Gt/a, but the rate has decreased greatly recently. The melting rate in the WA region is (-148.35±6.78) Gt/a, which shows an accelerating trend and is the main area of mass melting of the Antarctic ice sheet. The melting rate in AP region is (-22.01±1.44) Gt/a,and the change is  relatively stable.

We compare observation data of Wuhan and Lhasa superconducting gravimeters with free oscillations simulated by 14 different focal mechanisms of the 2015-09-16 Illapel earthquake. The focal mechanism solutions of the Illapel earthquake are analyzed and constrained by spherical normal modes in 1.5-5.3 mHz frequency band. We compare observed value with simulated value to search the more accurate scalar seismic moment and fault dip angle based on the optimal focal mechanism solutions. The results show that the scalar seismic moment of the 2015 Illapel earthquake is (3.0±0.2)×10²¹ Nm, corresponding to M_W8.3, and the optimal dip angle is 19°. This shows that the focal mechanism solution of Illapel earthquake can be evaluated based on superconducting gravity observation, and the reliable magnitude can be obtained by inversion based on long-period seismic wave signals or multiple observation data.

This paper investigates the relationship between the extreme point coordinates of gravity gradients created by submarine and the vertical distance from the submarine to the observation point. Through statistical analysis, we find that, except for V_zz, the other gravity gradient components have multiple extreme points. Numerical results also show that the Y-coordinates of the extreme points of V_xx and V_xz, the central extreme points of V_yy and V_zz do not change with the changes of observation height. The X-coordinate of the central extreme point of V_xx and the extreme points of V_yy,V_yz and V_zz are all non-linear with observation height, but the correlations between X-coordinates of these values and the observation height are not strong. The X-coordinate of extreme points on both sides of Vxx, X-coordinate of extreme points of V_xz, coordinates of extreme points of V_xy,Y-coordinates of extreme points on both sides of V_yy and Y-coordinate of extreme points of V_yz are linear with the observation heights. Finally, based on the relationship between the extreme points and the depth of the submarine, the feasibility of using the extreme point coordinates to inverse the depth of the submarine is verified.

We research how to obtain the optimal weight value in flow gravity observation data processing, which can be used to calculate gravity value. In the processing, we use the least-square method to solve the overdetermined equations consisting of the weight coefficient and the observations. The results show that the accuracy of the point value derived from the equal-weight method is not good enough. However, it contains more information for gravity anomaly seismic analysis and prediction. Although the accuracy of the point value solved by the unequal-weight method is better than the equal-weight method, it contains less information which may inhibit gravity anomaly seismic analysis and prediction. Finally, the results obtained from the least-square method not only have higher accuracy of the point value, but also is the best among the three methods, which can be used to analyze and predict the earthquakes with magnitude large than M_S4.0.

We explore the relations among the phase travel time, epicentral distance and focal depth by using theoretical seismic phase travel time tables. Results show that seismic phase varies when changing the epicentral distance or focal depth, there exists positive or negative correlations between them, and part of seismic phase travel time will truncate as epicentral distance or focal depth increases. These laws can offer a convenient approach to analyze the earthquake event.

In order to extract the trend turning point of time series, we propose an improved algorithm based on the combination of vector turning angles and extreme points applied to the analysis of seismic observation data. Combined with the corresponding rules of earthquakes, we evaluate the seismic prediction effectiveness of the XM₁-XM₂ line of Xiaomo mobile leveling, located in the northern Shanxi fault depression. The results show that: 1) The algorithm can be used to automatically extract the trend turning points of the time series, improving the efficiency of manual discrimination, and achieving the quantitative identification of turning points; 2) From the perspective of data statistics, the XM₁-XM₂ line has a good corresponding relationship with M>4.5 earthquakes within 200 km. The evaluation result of prediction effectiveness is R=0.63(R₀=0.43); 3) The seismic inflating rate of this line after 2000 is higher, probably related to the stress change caused by the far field effect from strong earthquake.

This paper proposes to use GPS time series predicted by deep learning to study earthquake precursors, taking the earthquake of M_S6.4 in Menyuan, on January 21, 2016 as an example. To obtain a high-precision GPS time series prediction model, the LSTM neural network is trained with GPS time series of historical non-seismic time series of Menyuan station(QHME), Minle station(GSML) and Gulang station(GSGL) near the epicenter, and then the GPS time series of non-seismic time series and the period of time before the earthquake in the region are predicted retroactively. Through comparative analysis of the predicted time series and the real time series, we find that most indexes of the similarity between the two time series before the earthquake are lower than those of the time series without the earthquake, which indicates that the predicted time series before the earthquake is obviously different from the real time series. Meanwhile, considering the trend anomaly of the time series before the earthquake, the abnormal time period is considered to have occurred. The three stations have multiple abnormal dates in E,N and U directions, and different stations have the same abnormal date. The discovery of abnormal periods and abnormal dates indicates that earthquake precursors have been explored.

In order to study the Quaternary activity characteristics of the middle section of Liaocheng-Lankao fault, we use the shallow seismic exploration and borehole combined section to detect the fault. We arrange five shallow seismic exploration lines and one borehole combined geological section are arranged across the fault. The borehole combining geological section reveals that the buried depth of the breakpoint on the fault is 61.4-64.5 m. Combining with the chronological results, the latest age of the middle part of Liaocheng-Lankao fault is the early late Pleistocene.

Predicting slope settlement in open-pit mines is an important means to grasp the trend of slope movement and guarantee the safe operation of the mine. Aiming at the problem that for the UBGM(1,1)-Markov model, two neighboring values may be assigned to different states, leading to deviations in predicted values; combined with fuzzy classification theory, we propose an unbiased grey-Markov model based on fuzzy classification model(FC-UBGM(1,1)-Markov). First, the residual correction is performed on the UBGM(1,1) model; the relative residual sequence of the fitted values after the correction is used as the Markov chain to divide the interval, and the membership function of the fuzzy classification is used to calculate the fuzzy vector of the relative residual. The accuracy of this prediction model is analyzed through actual cases. The experiment results show that, compared with the traditional UBGM(1,1)-Markov model, the predictive power of the model in this paper is better.

Considering the influence of gross error on three-dimensional surface deformation based on multi-LOS D-InSAR technology, ascribing gross errors to random model, we propose a method of the robust estimation of the three-dimensional surface deformation. We calculate the three-dimensional deformation using the least square method, and pre-residuals of measurements are obtained. Then, we establish the function between the least squares residuals and the unit weight variance. The weight of InSAR measurements are calculated from the unit weight variance. Based on the equivalent weight principle of the weighted iteration method, we process the robust estimation of the three-dimensional surface deformation using IGGⅢ weight function. We verify the feasibility and precision of the proposed method in a real data experiment based on the case of 2009 L’Aquila earthquake. The verification results show that the proposed robust estimation of 3-D surface deformation can effectively eliminate the influence of the gross error.

In this paper, we obtain the surface deformation rate of the southern margin of Ordos block using InSAR technology. This provides a basis for detailed analysis of different types of deformation features in the study area. The results show that there are multiple deformation funnels in the middle of the study area, and the urban area of the southern basin presents large-scale subsidence and uplift. The movement of the Qishan-Mazhao fault is left-lateral strike slip, and there are different movements on both sides of the Kouzhen-Guanshan fault. Based on remote sensing images and field survey data, it is determined that the deformation funnel in the middle area is caused by mining. The subsidence of Sanyuan county in the basin is mainly caused by underground pumping. The surface uplift in Fufeng county and Pucheng county are related to the rise of groundwater levels.

One problem in using the quadratic polynomial model for removing orbital errors is that it is necessary to assume the distribution properties of other interference phase. So, a method based on wavelet multi-scale analysis is proposed to remove orbital errors. Based on long wavelength and low frequency characteristics of orbital error phase, the method filters the phase with shortest wavelength compared to the orbital error in different scale spaces. Then, the robust least square method is used to estimate the parameters of the quadratic polynomial model in order to reduce the influence of residual terrain error phase on orbital errors polynomial fitting. The results show that the corrected interferograms contain less trend error, with better removal effect and higher reliability.

In order to analyze the impact of the GPS satellite P1-C1 differential code biases(DCB) on the estimation of satellite-based augmentation system(SBAS) corrections, GPS C1-P2 dual-frequency measurements of the monitoring stations in mainland China are used to generate the GPS SBAS clock-ephemeris corrections and the corrections are used in a standard positioning test. According to the results, there are significant differences between the estimated satellite clock corrections with and without P1-C1 biases. The positioning results show that taking off the P1-C1 DCB during the SBAS corrections estimation and SBAS users positioning can reduce the GPS C1 code SBAS users 95% positioning errors from 1.94 m to 1.45 m and from 3.82 m to 3.14 m in the horizontal and vertical directions, respectively, indicating a 19% reduction in three-dimensional positioning errors compared to those not taking off the biases. For C1-P2 dual-frequency SBAS users, the P1-C1 DCB impact can be eliminated as long as the processing of P1-C1 DCB in users positioning is consistent with the SBAS corrections estimation.

First, this paper briefly gives the AOD processing model based on inter-satellite ranging observations. Then, based on the real inter-satellite ranging data of the 18 MEOs of the BDS-3 basic system, the paper performs an autonomous orbit determination processing and performance analysis. The analysis results demonstrate that BDS-3’s ISL ranging function operates stably and has good continuity, the available ISL number of a single satellite is about 8.5, and the PDOP is about 1.34, the centralized autonomous orbit determination processing for 30 consecutive days is normal and stable, the average RMS of the orbital URE of all 18 satellites is 0.47 m, and the average RMS of the constellation relative time synchronization error is 0.31 ns when compared with precision orbit and clock products.

We derive the triple-frequency ionospheric-free parameters and minimum noise line expression using the space geometric principle. We compare the positioning accuracy and convergence speed of triple-frequency and dual-frequency ionospheric-free models using data from five static observation stations and Beidou triple-frequency observation data of measured sports car. The results show that under static conditions, the position error of triple-frequency PPP is 3.75 cm, the standard deviation is 2.06 cm, and convergence time is 109.6 min, which is 22.3%,19.8% and 22.1% higher than the performance of dual-frequency PPP, respectively. Under dynamic conditions, the position error of triple-frequency PPP is 15.21 cm and the standard deviation is 12.89 cm, which is 42.4% and 26.8% higher than the dual-frequency PPP, and the convergence speed is better than that.

Based on observation data from the GRW1, ZHON and the surrounding 13 IGS stations in 2018, we compare and analyze the effects of different cut-off elevation angles, mapping function models and global ocean tide models on GNSS coordinate accuracy. The results show that the GNSS coordinate presents the highest accuracy when the cut-off elevation angle is 7°. Along with the increase or decrease of the cut-off elevation angle, the accuracy will decrease gradually. The double difference positioning accuracy calculated by VMF3 model is better than that calculated by the NMF, GMF and VMF1 models, the accuracy of the precise point positioning calculated by VMF3 is equivalent to that of GMF and VMF1 models. The effect of ocean tidal load on GNSS coordinate solution is subjected to the coordinate directions, and can reach the cm level in the elevation direction. The differences of the GNSS coordinates calculated by different ocean tide models can be disregarded.

This paper focuses on the problem of deviation of seafloor control point coordinate solution caused by inaccurate measurement of sound velocity profile when using the sailing-circle positioning method. First, the effect of uncertainty in sound velocity on the ranging error are introduced. Then, the ranging error is divided into four parts: background sound velocity error, ranging random error, long-period term and short-period term of ranging error. The influence of these four parts on the control point coordinates are shown through analyzing the coordinate correction equation. The theoretical results are consistent with the simulation experiments.

Aiming at the shortcomings of traditional feature-based coarse registration with low efficiency and many mismatches, we propose a registration method based on feature space matching. We extract the feature space using a simplified PointNet model. We take optimized point cloud PPF information as input and calculate the Euclidean distance according to the extracted feature space vector to filter out matching points. We eliminate the mismatched points to complete the coarse registration through RANSAC, and use ICP to realize fine registration. The results show that the proposed algorithm combined with ICP greatly improves the registration efficiency compared with FPFH and SHOT algorithm, and RMSE of the registration result is smaller.

We propose a Gaussian mixture extend Kalman filter (GMEKF) algorithm for non-Gaussian colored noise processing to solve the random model mismatch problem caused by non-Gaussian colored noise in GNSS/SINS tightly-coupled system. We discuss the approximation of non-Gaussian noise by the Gaussian mixture model and the principle of GMEKF. To further improve the performance of the GMEKF algorithm, we use state amplification and measurement difference to process the colored noise components in non-Gaussian noise. The experimental results show that the proposed algorithm outperforms GSEKF algorithm in terms of random model, and its estimation accuracy is better improved in GNSS/SINS tightly coupled integrated system under non-Gaussian colored noise environment.

General formulae, based on a general function model and the theory of estimating variance components of Helmert type, are derived in this paper in order to estimate different variance components from same kind of observation. The simplified formulae from general formulae and some special cases are also given.