In the traditional RBF neural network model in the GNSS height fitting, the fitting accuracy is relatively low, the stability is relatively poor, and the correlation factors need to be set artificially in advance. This paper adopts the improved adaptive weight particle swarm optimization algorithm and MATLAB RBF newrb. The network function newrb combines to realize the automatic optimization of the number of hidden nodes and SPREAD in the RBF neural network function model, and improve the accuracy and stability of the algorithm in GNSS height fitting. Through the example analysis, the method has high fitting precision and can reach mm precision. Compared with the traditional quadratic polynomial model, the accuracy is improved by 17% and the stability is good. It has important reference value for accurately solving GNSS height anomaly.

In this paper, we process and analyze, by wavelet decomposition, the time series of ground-based GNSS precipitable water vapor (PWV), atmospheric pressure and zenith tropospheric delay (ZTD). Based on the actual precipitation of rainstorms, the results show that the wavelet high-frequency decomposition coefficients of one-hour interval PWV and ZTD are close to each other, and the characteristic information of rainstorm prediction can be extracted from them. The high-frequency ZTD can be used to replace PWV for wavelet analysis. In ZTD with frequency between 30 minutes and 1 hour, the forecast time information should be searched at level 1~3, the frequency below 30 minutes should be searched at level 3~5, the forecast threshold of db4 wavelet decomposition PWV can be set to -1.2, the forecast threshold of db4 wavelet decomposition ZTD can be set to -0.007, and the forecast threshold of db2 wavelet decomposition ZTD can be set to -0.01.

VLBI data processing contains real-time and after-action calculation modes.  In VLBI real-time mode, tropospheric delay correction can provide forecast value, and a high precision tropospheric empirical model is needed to realize the real-time correction of tropospheric delay. Currently, various applications require high-precision tropospheric empirical models to achieve real-time correction of tropospheric delay. In this paper, the IGS zenith tropospheric delay (ZTD) sequence and the ERA5 grid data integration ZTD sequence from 2010 to 2012 are used to establish empirical models on four VLBI sites in China as Local_ERA and Local_ZTD respectively. Based on the 2013-2014 IGS site ZTD, the two improved models are compared with the global GPT2w and SHAO-Gm models. The results show that the improved Local_ERA and Local_ZTD models have similar precision. The average accuracy of the model has improved at four VLBI sites, compared to GPT2w and SHAO-Gm, especially in the Beijing station with strong seasonal variation of water vapor. The average accuracy of Local_ERA is slightly higher than that of Local_ZTD, which is 7.90% higher than that of GPT2w model, and 21.26% higher than SHAO-Gm model.

When discussing the correlation between precipitable water vapor (PWV) and fine particulate matter (PM_2.5), traditional methods do not consider the impact of non-haze weather information contained in continuous data. So, this paper presents two data extraction standards: time standard and air quality index (AQI) level standard, which are used to obtain the corresponding PWV and PM_2.5 sequence during haze. In order to solve the problem of discontinuity after data filtering, a non-parametric Spearman rank correlation coefficient（ρ） is introduced in this paper. By dealing with the discontinuous and non-equidistant PWV and PM_2.5 sequence in different levels of the air quality during the haze-prone period in Beijing from 2014 to 2016, we learn that the average value after filtering of the first and fourth quarters in the three years is 0.661 3 and 0.628 0 respectively, and the overall average is 0.644 7, which indicates that the PWV and PM_2.5 sequence have a monotonous and positive correlation under hazy weather. The correlation coefficients of both are small under the traditional analysis method (unfiltered), indicating that the analysis result is more specific and accurate after the data is selected.

We propose a new EMD denoising method to solve the problem that the K value of the demarcated intrinsic mode function (IMF) cannot be determined directly in the process of Empirical mode decomposition (EMD) denoising when the number of IMF components of high frequency noise is less than the number of low frequency IMF components. This method uses an average period and energy density product index method to automatically determine the K value of the demarcated IMF, reconstructs the IMF components of high frequency noise, and subtracts the reconstructed noise from the original signal. The method is verified using the simulated data and the measured GPS elevation time series data of BJFS station. The experimental results show that the proposed method can directly determine the K value of the demarcated IMF and reduce the computational complexity. It was more reliable than the traditional EMD method in the noise reduction of GPS elevation time series.

In this paper, we analyze the feature of ultra-wide band (UWB) pseudo range, which is generated by method of time of flight (TOF). By applying Kalman filter and its transformation to the original TOF measures, we detect and remove measures with error as well as lower the noise of TOF measures. We build a model to correct system error of TOF measures by comparing it with known distance. The positioning result shows that as system error gets well corrected, the precision of UWB positioning reaches a level of 10 cm in static mode, and a level of 0.2 m in kinematic mode, while the path of object keeps smooth.

Based on continuous observation data from 59 GPS stations in Yunnan since 2011, the time series of surface strain anomaly mesh changes is obtained. The dynamics and geological tectonic background of the anomalous grid region, the characteristics of fault activity, and the type of focal mechanism of earthquake events are combined to analyze the spatial and temporal distribution characteristics of regional anomalies, as well as the relationship between crustal deformation anomalies and seismic events. The Dêqên earthquake is used as a seismic case to verify the effectiveness of the seismometric analysis method based on strain sequences. The results show that, based on the long-term background characteristics of the surface strain in the macroscopic analysis, the analysis method of the relationship between the short-term anomaly of surface strain and the earthquake event based on the nature of regional fault activity, that the strain time series analysis has certain scientific rationality. Possibly, for some earthquakes such as the Dêqên earthquake, there were effective predictive signals on the eve of the earthquake.

Based on the continuous observation data of GNSS in Yunnan since January 2018, the displacement field is obtained by high-precision data processing software (GAMIT/GLOBK), and the Kriging interpolation method is used to mesh the interpolation to obtain uniform distribution. We ascertain the displacement field, calculate strain, obtain surface strain information, dynamically analyze the surface strain variation characteristics of Yunnan in 2018, and explore the intrinsic relationship between the two M5.0 earthquakes in Tonghai and Mojiang M5.9 earthquake. The results show that there are significant backgrounds of strain accumulation before the two M5.0 earthquakes in Tonghai and Mojiang M5.9 earthquake, and there is a process of regional strain field adjustment in the short term before the earthquake. The two may be strong tensile and strong compression regional strains under the dual factors, the product of the changing process. The difference is that the Mojiang M5.9 earthquake changed the regional characteristics of strong extrusion and strong tensile joints bounded by the Shuangbai-Xinping-Mojiang strip, which had a substantial impact on the overall regional surface strain pattern in Yunnan.

We obtain the land subsidence rate of north China plain and east China through data processing, based on the radar altimetry technology. The geophysical parameters and environmental corrections are optimized in the study. We use the high-precision SRTM model to correct the slope of the terrain, then use the improved threshold algorithm to improve the observation accuracy of the altimetry data. The results show that, comparing the vertical motion rate derived from satellite data with those calculated by GNSS reference station data, that the deviation is -3.4±9.1 mm/a and the correlation coefficient is 0.88. With the threshold (TR) and modified threshold retracking method (MTR), the deviation decreases to -3.2±5.5 mm/a and -2.9±4.1 mm/a, and the correlation coefficient rises to 0.94 and 0.97 respectively. The experimental results show that the satellite altimetry can be applied in land surface subsidence monitoring research, particularly in uninhabited remote areas where GNSS and traditional level of monitoring data are absent.

Based on Sentinel-1A data from January 2016 to July 2018, we obtain the ground deformation information of the main urban area in Nanchang using PS-InSAR and SBAS-InSAR time series processing methods, compare the two monitoring results, and analyze the causes of uneven ground deformation. The results show that the monitoring results of the two time series technologies are highly correlated. The deformation trend of the main urban area of Nanchang City is northeast uplift and the southeast sinking. The spatial distribution of the deformation zone includes the Meiling uplift area, Nanchang west railway station subsidence area, Ganjiang east bank subsidence area, Dengjiabu subsidence area and Nangang subsidence area, which are mainly affected by factors such as geological structure, aquifer medium, groundwater exploitation and urban construction.

Taking the Xieqiao coal mine in Yingshang county of Anhui province as an example, we use the InSAR technique to detect the surface deformation results of the mining area from 2007 to 2011. We use the sill model to simulate the deformation of the mining area and analyze the subsidence funnel. The developmental state provides an important reference for regional land subsidence risk assessment. The results of InSAR deformation show that there are many subsidence funnels in the study area, which are generally distributed in the east-west direction. With the passage of time, the subsidence center continues to move and the range of subsidence gradually expands. Combined with remote sensing images, it is found that the formation of the settlement funnel and the collapsed water area is consistent in time, and the spatial distribution is also highly correlated.

Using two recently S-wave tomography models, SEMUCB_WM1 and S40RTS, we make numerical simulations of the instantaneous mantle convection in the three-dimensional spherical coordinate system, yielding global large-scale core-mantle boundary (CMB) topography relief with an amplitude of approximately -5~5 km, with a distribution mainly characterized by the uplifts of the core-mantle boundary under the Pacific and south Africa and depressions around those areas.

Based on 86 M_L≥2.5 seismic events waveform recorded in Jiangxi since 2009, we use genetic algorithm inversion to obtain the non-elastic damping coefficient in site response of each station, calculating the source parameter on the basis. The results show that the frequency dependent non-elasticity coefficient Q in Jiangxi area is estimated as Q(f)=323.1f^{0.505 9} and the site response of most stations is flat in frequency domain, consistent with the bedrock property of the stations. We find a linear relationship between M_L and these seismic moment M₀ in the single-logarithmic coordinates, a negative correlation between seismic moment and corner frequency, a non-significant correlation between seismic stress drop and seismic moment, and a significant double logarithmic relationship between source radius and stress drop.

According to the sP and pP characteristics of the seismic wave Sp phase and the teleseismic depth of the basement interface of the near-seismic sedimentary layer, we analyze the focal depth of the February 12, 2018 Yongqing M4.3 earthquake. F-K wave number and frequency method are used to fit. The near-seismic theoretical waveform and Teleseis method fits the far-seismic theoretical waveform and we compare it with the actual waveform to test the focal depth. The results show that the focal depth of the Yongqing earthquake is in the range of 16 km to 17 km. From the analysis of the location of the earthquake and the depth of the source, the earthquake occurred in the upper middle crust, similar to other seismic events in the area.

The fixed point gravity non-tidal change data of the sinking balcony is stable, but the data have risen significantly for five consecutive months since June 2017, and the rate of increase is relatively large, with an amplitude of about 5 μGal/month, breaking the steady state of returning from the power failure in 2015. We investigate the instrument observation system and the regional geological characteristics: the GPS data began to decline in vertical component in May of the same year; computational analysis of GPS vertical changes cause the value of heavy forces (-1.714 μGal/mm) to be much smaller than the change in gravity; the station irrigated the flowers with water to do the gravity model simulation and calculated the disturbance change only 0.218 1 μGal, much less than the 5 μGal per month magnitude change disturbance. Through quantitative calculation and analysis of gravity changes caused by GPS vertical direction, calculation of water well pumping forward model, it is found that changes in external influences are not enough to cause the gravity and non-tidal anomalies; according to the comprehensive analysis 14.781 9 μGal, the gravity non-tidal change anomaly is an earthquake precursor anomaly. It thus provides a reliable basis for subsequent earthquake prediction.

In this paper, we select eight GRACE temporal gravity field models as research objects, including CSR05, GFZ05, JPL05, ITSG-Grace2016, CSR06, GFZ06, JPL06 and ITSG-Grace2018. The terrestrial water storage (TWS) in the Pearl river basin (PRB) from January 2005 to December 2012 is derived from GRACE temporal models processed by the Swenson de-striping filter and 300 km Gaussian smoothing filter algorithm. Finally, the ITSG-Grace2018 model, GLDAS hydrological model, precipitation data and measured groundwater data are selected to comprehensively analyze the variations of TWS in the PRB. The results show that: 1) The accuracy of the release-2006 GRACE temporal gravity field models released by the CSR, JPL and GFZ is significantly improved compared with the release-2005 models. The accuracy of the ITSG-Grace2018 model is also improved compared with the ITSG-Grace2016 model and the difference between the new versions of the temporal gravity field models is smaller. 2) The TWS of the PRB derived from the ITSG-Grace2018 model show an overall upward trend during this period, and seasonal changes are consistent with GLDAS hydrological model, precipitation data and measured groundwater data.

This article improves the long-term mean ratio method from the following aspects: First, the abnormal term of the long-term mean ratio method is not included in the denominator of the normal term, highlighting its ability to behave abnormally. Second, the amplitude of the 4th power of X is used as the feature function, making the feature function reflect the characteristics of the phase arrival time. Third, the problem of picking up the phase becomes the problem of finding the maximum value of the characteristic function. Two-way recording jointly picks up S-waves. Fourth, it is proved that the difference between the upper and lower thresholds is obvious when using amplitude quaternion as a characteristic function to pick up seismic phases, and the threshold value of arrival time of seismic phases can be defined as two times the lower thresholds. Finally, it is clearly specified that only three records are used for the short time of the molecule. When the peaks (troughs) of the first arrival and the previous and next maximums, the length-to-time mean ratio must get a maximum, and the time corresponding to the middle data point is the first arrival of the seismic phase. When improved methods are used to pick up 100 seismic records with obvious phases, they all achieve high accuracy. The method in this paper can be regarded as an extension of the time-average ratio method. After the P-wave arrival threshold is determined, it can be used to automatically pick up the P-wave arrival in earthquake early warning.

In this paper, we study the original observation curve of the minute value of the first component of the 2007-2014 strainmeter at Guza station. The statistical results show that the daily and monthly anomalous total amplitude, frequency and time are significantly increased before the Wenchuan earthquake. The daily and monthly cumulative value curves increase rapidly, and the rate slows down after 2008. The maximum phase difference is 10, 9 and 4 times. So, it has a strong corresponding relationship with the Wenchuan earthquake. However, the process of the subsequent earthquakes in Lushan and Kangding does not reappear. According to the results of in-situ stress measurement and visual stress analysis in the Longmenshan area, this phenomenon has been explained to a certain extent.

This paper presents tilting calibration methods of air-sea gravimeter scale value in detail. We use the self-developed CHZ-Ⅱ air-sea gravimeter to calibrate the experimental scale value and get the final weighted average of the scale value.

To quantitatively estimate the various components contained in the observation sequence, deepen understanding of the physical meaning of observation, evaluate the observation environment, observation quality and monitoring capability of topographic change and seismic topographic change of the station, deepen the understanding of the observation data, and accurately identify the pre-earthquake anomalies, this paper takes the thermal body strain in Wenquan station as an example, selects the observation data of the three elements of thermal body strain in Wenquan station, auxiliary observations and meteorology, and uses the methods of Pertesv’s filtering, wavelet analysis and correlation analysis, etc. The influencing factors and characteristics of the periodic changes of the thermal body strain observation in Wenquan station are analyzed. The results show that: 1) The influencing factors of the annual periodic changes of the thermal body strain in Wenquan station may be at the borehole water level, and the thermal spring body strain phase lags the water level by about 31 days. 2) Air pressure is the main influence factor of thermal body strain monthly wave in Wenquan station. 3) Solid tide is the main influence factor of daily wave and semi-daily wave on thermal body strain in Wenquan station. 4) Body strain in Wenquan station has strong linear correlation with water level, air pressure and solid tide.