Based on the data of ground tilt within 500 to 600 km from the epicentre of Wenchuan M8.0, Yushu M7.1, Lushan M7.0, Jiuzhaigou M7.0 and Maduo M7.4 earthquakes that occurred in the north-south seismic belt since 2000, the anomaly analysis of tidal factors, rate analysis, trend turning method, annual variation method and the change characteristics of azimuth and inclination of ground tilt data before the earthquake are carried out. The results show that the tidal factor exceeds 2 times the mean square deviation anomaly about one year before the 5 M≥7 earthquakes, and the anomaly duration is mostly 1 to 3 months. The rate analysis method is suitable for short-term anomaly index extraction, while the trend turning method and the annual variation method are more suitable for medium-and long-term prediction. The magnitude extracted by the trend turning method and calculated by empirical formula is closer to the actual magnitude. The change of dip angle and azimuth angle is more prone to quasi-synchronous anomalies in places far from the epicenter before the earthquake.As the distance to the epicenter decreases, the number of anomalies diminishes, and most of them are single anomalies in either azimuth angle or dip angle.According to the characteristics of ground tilt anomaly and magnitude prediction at present, it is considered that the entropy of ground tilt amplitude factor at present is mainly over-threshold anomaly, and the anomaly of trend turning extraction is concentrated at the junction of Gansu, Qinghai and Sichuan, and the predicted magnitude is high. The regional stress level at the junction of Gansu, Qinghai and Sichuan is still high after the Jishishan M6.2 earthquake. The distribution characteristics of the azimuth angle and dip angle of the ground tilt are similar to those observed before Wenchuan M8.0 and Lushan M7.0 earthquakes.

Early research on broadband seismometer azimuth mainly based on the P-wave particle polarization principle and calculates the angle corresponding to the minimum value of P-wave energy on the lateral component to obtain the angle between the north-south direction of seismometer and the geographic north pole. In addition, the elliptical motion characteristics of Rayleigh waves can be used to estimate the seismometer azimuth of stations with azimuth deviation. We estimate the seismometer azimuth deviation of 20 stations of CENC based on the two different methods. The results show that the azimuth deviation calculated by the two methods is in good agreement, indicating that Rayleigh wave analysis can be appropriately added in future seismometer azimuth detection.

Based on the images from Gaofen-1 satellite, taking the first section of the Three Gorges reservoir as an example, 160 landslide samples are visually interpreted and divided into training and validation samples according to the ratio of 9:1. Then, landslide automatic identification models are constructed using Mask R-CNN and Faster R-CNN algorithms. To further compare and analyze the performance of the two models under different sample ratios, calculations are performed using sample ratios of 8:2, 7:3, and 6:4. The results show that the recognition results based on Mask R-CNN model are better than Faster R-CNN in three indicators, including precision, recall and F1 score. Moreover, cross-validation proves that the performance of Mask R-CNN model is more stable.

In this paper, we collect 1 Hz high-frequency data from multiple GNSS ground reference stations near the epicenter of the Jishishan earthquake on December 18, 2023, and use PRIDE PPP-AR and TRACK software for dynamic PPP calculation and high-precision static data processing. The coseismic deformation displacement fluctuation and permanent deformation displacement of the GNSS reference stations are obtained. Then, we analyze the deformation impact of the earthquake on the GNSS ground reference station at the epicenter. The results show that PRIDE PPP-AR and TRACK software can both calculate the coseismic deformation displacement impact of the earthquake on the reference station. The static calculation results show that the earthquake caused a permanent deformation displacement of about 18 mm in the horizontal direction at LXJS station (5.3 km away from the epicenter), and the impact range of this earthquake on the stability of the GNSS reference station is about 50 km. The rapid deformation analysis method and results can provide reference and data support for disaster prevention and mitigation, as well as real-time navigation and positioning services.

To study the activity characteristics and patterns of the landslide, this paper uses stacked interferometric synthetic aperture radar (InSAR) based on ascending and descending track C-band Sentinel-1A data to obtain the deformation rates of the Cheyuping landslide from January 2020 to December 2021 along the slope direction and in the vertical direction. We obtain the landslide displacement time series evolution results. The results show that the maximum deformation rate of Cheyuping landslide is more than -90 mm/a along the slope direction and more than -40 mm/a in the vertical direction, and the deformation of the landslide is larger at the leading edge and middle part of the landslide, and smaller at the trailing edge, which is characteristic of the slip-type landslide. According to the analysis of rainfall data and time series results, rainfall has a certain influence on the landslide movement, showing seasonal accelerated deformation characteristics. At the same time, the geological and stratigraphic lithology of the landslide area and the change of the water level of the Lancang river also accelerated the landslide activities to a certain extent. This study can provide technical reference for the interpretation of landslide deformation mechanism and disaster monitoring and early warning in the canyon reservoir area.

The water level change series of lakes in the Qinghai-Xizang plateau from 2003 to 2022 are extracted using the data of ICESat, Cryosat-2 and ICESat-2. Taking Qinghai lake as an example, the three retracking algorithms of Cryosat-2 LRM(Ocean-CFI, UCL Land-ice and OCOG) are compared and analyzed, and the results show that OCOG algorithm is the best. The accuracy of the time series of lake water level changes extracted from satellite altimetry data is evaluated by using the hydrological station data of Qinghai lake, Nam Co, Mêmar Co and Lumaqangdong Co, and the results show that the RMS of the difference between the water level change time series of Qinghai lake and the measured results of Xiashe station is only 0.092 m, and the correlation coefficient between the water level change time series and the measured results of Nam Co is 0.989, and the accuracy analysis of different measurement techniques in the same time period shows that the accuracy of the Cryosat-2 SARIn measurement mode is slightly higher than that of ICESat-2. The water level changes of 106 lakes in the Qinghai-Xizang plateau from 2003 to 2022 are extracted, and the water level change trend is analyzed, and the results show that the water level of 19 of the 106 lakes show a downward trend, and the water level of 83 lakes show an upward trend.

The road in the open-pit mining area is narrow, with many curves, rubbles, and bumpy roads. The special surface closed loop leads to system model anomalies and measurement noise uncertainty problems during positioning of transport vehicles. To address the above issues, we propose an SVD-AUKF algorithm with a noise estimator. The algorithm suppresses the pathological matrix that occurs during the filtering process by singular value decomposition of the covariance matrix, estimates the measurement noise using the Sage-Husa estimator, reduces the system state error, and introduces an adaptive factor to correct the system model error in real time to suppress the filtering divergence. We apply and test the proposed SVD-AUKF algorithm to the GPS/INS integrated navigation system model on a vehicle in a mining environment. The results show that the new algorithm has good applicability, with position accuracy improvements of approximately 50.69%, 51.20%, and 48.54% compared to the AUKF algorithm; speed accuracy improvements of approximately 31.24%, 33.83%, and 31.30% in E, N, U directions, which can effectively improve the filtering performance and increase system positioning accuracy.

By utilizing satellite time-monitoring data to mitigate the impact of satellite-side and transmission path errors in standard single-point positioning, the timing stability and positioning accuracy at the user end are improved. At the same time, the timing deviation of the user relative to the satellite navigation system is corrected to be relative to the national standard time. Taking GPS as an example for a short baseline experiment, the results show that in terms of timing, the mean timing deviation of the L1 frequency band was improved from -42.8 ns to 5.4 ns, and from -53.6 ns to 2.8 ns for the L2 frequency band; in terms of positioning, the mean positioning errors in the X, Y, and Z directions for the L1 frequency band were improved by more than 55%, and by more than 77% for the L2 frequency band. This proves that by using satellite time-monitoring data, users of the satellite navigation system can not only enhance the pseudo-code positioning accuracy to the sub-meter level but also obtain the deviation relative to the national standard time, achieving ns-level timekeeping of the national standard time.

In response to the imprecise localization of moving radiation sources in complex scenarios and issues related to the accuracy of the observation station's position and the geometric relationship with the target using the two stage weighted least squares(TSWLS) algorithm, we propose a passive radar centroid passive localization algorithm for moving targets based on Taylor expansion and the joint application of TSWLS. This method utilizes a TSWLS algorithm to determine the target's position and velocity. The obtained target parameters serve as initial values for Taylor expansion, constructing the positioning error equation. Through iterative optimization, the algorithm refines and solves for optimal target parameters. The proposed algorithm and TSWLS independently provide estimations, with the final result obtained through centroid localization. Simulation experiments show that, regardless of target speed, in comparison with traditional methods, the presented algorithm significantly improves robustness and positioning accuracy while reducing sensitivity to geometric relationships between the observation station and target.

On August 23, 2023, a M4.6 earthquake hit the Pulandian, Liaoning province. To describe the source characteristics of this earthquake, we explore its incubation and seismogenic mechanisms. In this paper we determined the focal depth of the Pulandian M4.6 earthquake, and calculate the focal mechanism solution, moment tensor solution and centroid depth of the earthquake, obtain the center of focal mechanisms of the earthquake. In the same, we analyze the relationship between focal mechanism and tectonic stress field, and fit the fault plane according to the results of small earthquake relocation. We preliminarily determine the seismogenic fault plane of this earthquake. The results show that the initial rupture depth of the Pulandian M4.6 earthquake is 12.0 km. The focal mechanism solution is strike: 50°, dip: 75° and rake: －169° for nodal planeⅠ, strike: 317°, dip: 80°and rake: －15° for nodal plane Ⅱ, the moment magnitude is M_W4.8, while the centroid is 12 km. The seismic moment M₀ is 1.796×10¹⁶ Nm, the moment tensor solution is M_rr: －0.004, M_tt: 0.946, M_pp: －0.942, M_rt: 0.017, M_rp: －0.305, M_tp: －0.125. The center of focal mechanisms solution is strike: 47.03°, dip: 79.04° and rake: －168.15° for nodal planeⅠ, strike: 314.75°, dip: 78.37°and rake: －11.19°for nodal plane Ⅱ. The relative shear stress and relative normal stress generated by the tectonic stress field acting on the nodal plane Ⅰ are 0.877 and －0.544; on nodal plane Ⅱ they are 0.911 and 0.161. The fitted seismogenic fault plane is strike: 148.91°, dip: 89.85° and rake: 26.47°. The analysis shows that the Pulandian M4.6 earthquake occurred on the Pulandian-Changhai NW tectonic belt. It is a natural earthquake that after stress accumulation occurs along the optimal nodal plane of the stress field and takes left-lateral strike-slip as the dislocation mode.