In order to explore the operating status and performance of the BDS-2 satellite clock at this  stage, based on the 365 days of precision clock offset data from the international GNSS monitoring and assessment system(iGMAS) in 2018, this paper introduces the Score test into the clock offset detection and combines the median method to control the data quality, making up for the gross error defect of the median method. Then, from the six aspects of frequency accuracy, frequency drift rate, frequency stability, model fitting residual, period characteristics and noise type, we comprehensively evaluate the relevant performance of BDS-2 satellite clock. The results show that: at this stage, the BDS-2 on-orbit satellite clock is in good operating condition, all performance indicators are normal, and the corresponding system services can continue to be provided. Among them, the frequency accuracy of the BDS-2 satellite clock is 3.15×10^-11; the daily drift rate is 1.59×10^-13; the frequency tens of seconds stability is 5.72×10^-14; the average accuracy of the model fitting residual is 0.593 ns; the GEO, IGSO, and MEO three types of satellite clock data have significant periodic characteristics, and the first and second main periods are related to their respective satellite orbit periods, which are about 0.5 times or 1 times their orbital periods respectively; the BDS satellite clock noise types are basically the same under different smoothing times, and are affected by WFM, FFM and RWFM.

Based on the precise ephemeris and clock product, we evaluate the orbit accuracy, clock accuracy and 3 kinds of signals in space ranging error(SISRE) of BDS-3 broadcast ephemeris. The results show that the broadcast orbit accuracy of BDS-3 satellites is obviously better than that of BDS-2 satellites. Radial RMS accuracy of BDS-3 satellites is better than 0.18 m, along-track and cross-track RMS accuracy is better than 0.6 m. The broadcast clock errors of BDS-3 satellites are maintained within 5 ns and are more stable than those of BDS-2. The RMS and 95% statistical accuracy of BDS-3 broadcast clock errors are 1.86 ns and 3.23 ns respectively, which are better than that of BDS-2 satellites. The RMS statistical accuracy of orbit-only SISRE, global-average SISRE and worst SISRE of BDS-3 satellites are 0.12 m, 0.58 m and 0.60 m respectively and the corresponding 95% statistical accuracy are 0.22 m, 0.99 m and 1.02 m, and both of them are significantly better than BDS-2.

In view of the extremes of the non-integrity events of the ground based augmentation system(GBAS), we study the integrity algorithm of GBAS. We give the calculation method of airborne protection level under H0 and H1 assumptions, and analyze the influences of the main error sources of two kinds of non-integrity events, false alarm and missed alarm. We carry out verification experiments, and the experimental results show that the accuracy of the position solution of the airborne terminal after differential correction is better than 1 meter, and its availability is greater than 99.999 9%, which meets the requirements of class Ⅰ precision approach and landing navigation. At the same time, we carry out simulations of non-integrity events, and the results show that the geometric distribution of satellite and ionospheric storm are the main error sources of false and missed alarms. In the future, class Ⅲ GBAS needs to expand the single constellation to multiple constellations including Beidou, and upgrade the single frequency to dual frequency. Among them, multiple constellations can optimize the geometric layout of satellites and dual frequency can eliminate the ionospheric storm impact.

We improve the accuracy of GPS mobile observation positioning using the time series of continuous observation stations within 200 km of the GPS mobile station, and discuss the reliability of GPS mobile observation results. The results show: 1) The standard deviation of velocity obtained by mobile observation decreases by 37.97% compared to continuous observation. 2) The deviation of measured value decreases by 38.9% on average after correction at TAIN and CASH sites.

Based on the dual frequency uncombined PPP model, ISB parameters are processed by constant, white noise and random walk models respectively. Static and simulated dynamic experiments are carried out by using 10 days data of 7 MGEX stations to analyze convergence time and positioning accuracy of 3 models. The results show that in terms of convergence time, the effect of the random walk and white noise models are the same, both of which are superior to the constant model; static and simulated dynamic methods increase by 15.4% and 29.4% respectively. In terms of positioning accuracy, the effect of the random walk model and white noise method are equivalent. Compared with constant method, the accuracy of E and U direction improve most obviously, increasing by about 77.7% and 32.2% in static state, and by about 66% and 43.5% in simulated dynamic positioning.

Based on the iterative least square method, we develop two empirical Tm models for Hong Kong region: T_m_hk1 and T_m_hk2, with vertical adjustment using the radiosonde data of Kings Park station during the 2012-2017 period. The precision and reliability of the developed models, Bevis and global pressure temperature 2 wet(GPT2w), over Hong Kong region are evaluated using the sounding profiles throughout 2018. Results show that T_m_hk1, which requires the surface temperature at the station, can achieve a high precision with annual mean bias better than 0.3 K and the root mean square error(RMSE) within 1.8 K. Compared with the Bevis formula and GPT2w model, the accuracy of T_m_hk1 model increased by 35.4% and 29.7%, respectively. The T_m_hk2 model without the requirement of the meteorological parameter can achieve the same accuracy as the GPT2w model, and annual mean RMS error of both models are better than 2.5 K. Bevis formula has the worst accuracy(RMSE=2.7 K) and a large negative bias of -1.8 K. From the analysis, it can be found that the precision of Bevis, T_m_hk2, and GPT2w models show an obvious seasonal variation. The overall precision of the models during summer is higher(RMSE=1.3-2.2 K) than that during winter(RMSE=3.0-4.4 K). Furthermore, T_m_hk1 model performs the highest precision and applicability during all seasons, with the RMSE ranging from 1.4-2.4 K.

Based on the existing weighted symmetric similarity transformation, only the case where the observation value contains random error is considered, and the case where the observation value contains the gross error is not considered. This paper further verifies that the weighted symmetric similarity transformation is not robust. Based on the weighted symmetric similarity transformation, the method of selecting weight iteration is adopted to make the robust weighted symmetric similarity transformation. The model obtains unit weight mean square error with robustness by the median method and utilizes the standardized residual to construct the weight factor function, to obtain a reliable parametric solution. Comparative analysis shows that: when the observations contain 4-6 gross errors, the method of this paper can be used to detect more data that may have gross errors, the weighting factors given are more reasonable, and the obtained parameter solution has higher accuracy and stronger stability.

In this paper, the authors used the waveform records of the 2006 to 2017 earthquake events in Shandong province, and the wavelet transform of three kinds of earthquake type: natural seismic, blasting and collapse waveform are carried out, and Shannon entropy features are extracted by support vector classifier LIBSVM. A series of experiments are designed to study the factors that affect the final classification effect. The results show that the length of signal window, the way of wavelet decomposition, the type of wavelet base, the type of vector machine and the type of vector machine kernel function all have some influence on the result of seismic classification. The combination of 2 000 seconds signal window length +db7 wavelet base+υ-SVC vector machine is used in the three groups with the highest recognition rate. The combination of several factors with high recognition rate can be applied to real-time recognition of earthquake type in the future to further improve the recognition rate of earthquake type and trigger accuracy.

This paper used Snoke method and cap method to inverse the focal mechanism solutions of the 14 earthquakes from August 2014 to March 2015, and analyzes the temporal and spatial changes. At the same time, we calculate the 14 M_L≥3.0 earthquakes by the PTD first arrival method, and compare the results with CAP depth search method. The results show that the 2014 Jinzhai earthquake swarm sequence is densely distributed between 115.50°-115.53°N, 31.50°-31.53°E, with no obvious seismogenic law in the time and space. The focal mechanism solutions of the 14 M_L≥3.0 earthquakes are basically the same, the azimuth of P axis is relatively consistent, and the dip angle is relatively high. It’s a strike-slip earthquake under the action of horizontal compression near EW direction and horizontal tension near NS direction. The results obtained by the two methods are similar, focusing on 2 to 5 km.

Based on geological structure of regions near the Xiannüshan-Jiuwanxi fault zone, we discuss the characteristics of seismic activity in the vicinity of the Three Gorges Reservoir before and after impoundment. The triggering relationship between M4.5 and M4.7 earthquakes occurred on 2014-03 and the influence of the two earthquakes on subsequent small earthquakes is further studied. The results show that the M4.7 earthquake may be jointly triggered by M4.5 earthquake and large pore pressure caused by water seepage. The stress disturbance of M4.5 and M4.7 earthquakes led to the increase of seismic activity in the study area, and about 66.9% of the subsequent earthquakes occurred in the area of Coulomb stress enhancement. Variation of static Coulomb stress caused by two earthquakes led to the increase of seismicity near the Xiannüshan fault zone. The seismicity near Xiannüshan fault zone will be above the background seismicity in the coming period. The activity of Jiuwanxi fault zone is relatively weak, slightly less than background seismicity and in the stage of stress accumulation.

On the basis of field investigation, the quartz particles in three gouge samples collected from Xuancheng-Jingting mountain section of Jiangnan fault zone, are observed and counted by transmission scanning electron microscopy(SEM). The results show that Jiangnan fault zone is an active fault zone, which has obvious activity in the Neogene and Quaternary. The activity began in the Miocene and reached its peak in the late Pleistocene. The main mode of activity is creep slip. In the Holocene, the faults continue to move in the way of stick slip. Seismic records along the fault show that the fault is still active until modern times. This conclusion is of great significance for correctly evaluating the Quaternary movement of the Jiangnan fault zone and preventing natural disasters in this area.

Based on geological survey data from the central urban area of Ji’nan, we calculate the Coulomb failure stress change (ΔCFS) induced by historical strong earthquakes in the north China region and investigate the influence on each fault in the Ji’nan area. The results show that the ΔCFS on the Miaolang-Jiaobin fault increased up to 1.1 kPa, which has the maximal impact. The stress on the northern section of Woniushan fault and Ji’nan-Sungeng fault increased up to 0.8 kPa and 0.6 kPa respectively. The activity of these faults may be slightly enhanced, but the stress changes are far below the seismic trigger threshold (10 kPa). The stress has only weak and negligible change in the west and east part of Qihe-Guangrao fault, and the impact is minimal. Comprehensive analysis reveals that due to the fact that the epicenter of historical strong earthquakes in north China is far from the study area, the impact on the main faults in this area is limited.

In this paper, we analyze the characteristics of segmental activity on the Jinshajiang fault zone using GPS horizontal velocity field and current small earthquake activity distribution data, and discuss the seismic risk. The results show that: 1) The activity of the Jinshajiang fault shows segmentation characteristics. The activity in the northern section is not obvious, but the middle and southern sections show obvious right-lateral strike-slip movement. The sliding rates are 4.9 mm/a and 5.5 mm/a respectively, and the blocking depth is about 20 km. 2) There are strain accumulations in the middle and south sections of the Jinshajiang fault, and the seismic risk cannot be ignored. 3) According to current crustal deformation data, the Jinshajiang fault is the northwestern boundary that controls the movement of the Sichuan-Yunnan rhombus block.

We reconstruct and extract the high-frequency stationary signals and low-frequency trend signals of Shanxi fault zone cross-fault deformation observation data using empirical mode decomposition(EMD). We analyze the earthquake precursory anomalies and their manifestations based on the high-frequency stationary signals reconstructed, and the results show that notable omen anomalies appear before the moderate-strong earthquakes occurred in Shanxi province and its adjacent areas. While there are a great number of abnormal sites before the strong earthquakes in the adjacent areas, which are widely spread and far from the epicenters, the abnormal sites before the moderate-strong earthquakes in Shanxi province concentrate close to the epicenters. We analyze the spatio-temporal evolution characteristics of fault deformation based on the low-frequency trend signal reconstructed, and the results show that the faults in Shanxi fault zone are dominated by inherited positive fault movement, but the fault movement characteristics vary by place and time.

The observation results of Gaoya leveling is abnormal from January 2017 to April 2018. In order to study the mechanism of this anomaly, based on the quantitative simulation by 2-D irregular load model and the qualitative and quantitative analysis of impact factors such as reservoir capacity, precipitation and underground water level, the following understanding is obtained: 1) The change of Gaoya reservoir capacity load has a weak influence on the Gaoya leveling, which is not the main interference factor of the Gaoya leveling. 2) The deeper reason for the abnormal change of Gaoya leveling is that the change of underground water level affects the inconsistent deformation of rock mass at both ends of the level through water-rock action. The subsequent changes of observation verify the rationality of the new understanding about the mechanism of the abnormal changes.

In the process of level retest data analysis, in view of the destruction of the benchmark point, the data continuity is poor and the utilization rate is reduced. In this paper, the vertical point variable of the same name is selected in the adjacent year. The distance, the interpolation point and the fault information at the observation point are used to determine the weight, construct a polynomial interpolation model, interpolate the vertical variables in the measurement area, enrich the data volume of the measurement area, and improve data continuity and utilization. We construct the Kalman filter model by constructing the state vector with the vertical shape variable, deformation rate and deformation acceleration rate of each interpolation value, and filtering the range of the measurement area. Using the filtering results, we analyze the vertical deformation characteristics of the Shanxi-Hebei-Inner Mongolia border area since 1984 and compare them with previous research results. The experiment proves the method is effective and can be applied to the study of earthquakes.

We are concerned with the limited application of L-band ScanSAR model for landslide identification. We research the estimation of ionospheric phase by range split spectrum method to improve the accuracy of InSAR monitoring, and propose the feasibility of using ScanSAR mode to identify landslides.

In this paper, we eliminate outliers in observation data by RANSAC algorithm, and the linear interpolation method is used to complete the data set. The relative gravity value between two points is extracted by overall projection calculation, and its accuracy and standard deviation are tested. The results show that the maximum residual value of dynamic gravity observation is 4.641 μGal, and the maximum repeatable standard deviation is 4.384 μGal, both less than 5 μGal. This method can obtain high-precision gravity observation data, and provides a new method for obtaining relative gravity values in complex environments.

In this paper, we inverse the spatial and temporal terrestrial water storage changes(TWSC) in the Three-River Source(TRS) region from 2006 to 2015 using the latest CSR data of GRACE RL06. The TWSC results obtained by RL06 are compared and analyzed with GLDAS hydrological model and TRMM precipitation data. The results show that the variation trends of terrestrial water and surface water in Three-River Source region between 2006 and 2015 are 5.2±1.2 mm/a and -3.8±0.9 mm/a respectively. Precipitation is closely related to the change of terrestrial water and is the main reason for the seasonal terrestrial water storage changes; permafrost, as a special aquifer, affects the hydraulic relationship between surface water and underground water. Combined with the surface freeze-thaw data, it is speculated that the permafrost activity causes the difference in the water storage of GRACE and GLDAS.

We develop a visual software system to rapidly process vibration data gained in linear array method. The main functions of the software include verification of field observation report, data format conversion, selection of effective timing data segments, array data cutting, extraction of dispersion curve, survey line display and other functions. The software can improve the speed of observation and data processing in linear array method greatly. According to the idea of this paper, the rolling observation data of triangle array can also be processed quickly.