Global navigation satellite systems (GNSS) have provided an excellent way to monitor micro-deformation in real-time. However, at local sites where landslides frequently occur, the environment can include complex surroundings with mountains, dense vegetation, and human settlements, which can severely degrade the accuracy of positioning with the GNSS technique. In this study, we propose an azimuth-dependent elevation weight (ADEW) model using an azimuth-dependent elevation mask (ADEM) to reduce the effects of multipath errors and improve the accuracy of real-time deformation monitoring in such environments. We developed an adaptive fixed-elevation mask to serve as the outlier of low precision observations at lower elevations for the ADEM, and then, we applied the weighted phase observations into the mitigation process for the effects of multipath errors. The real numerical results indicate that the ADEM model performs better than the conventional model, and the average improvements were 18.91% and 34.93% in the horizontal and vertical direction, respectively. The ADEW model further improved upon the ADEM model results by an additional 21.9% and 29.8% in the horizontal and vertical direction, respectively. Therefore, we propose that the ADEW model can significantly mitigate the effects of multipath errors and improve the accuracy of micro-deformation monitoring via GNSS receivers.

The Global Navigation Satellite System (GNSS) is currently one of the important tools for landslide monitoring and early warning. However, the majority of GNSS devices are installed in mountainous areas and a variety of vegetation. These harsh environments lead to defective signals at high elevation angles, rendering real-time successive and reliable positioning results for monitoring difficult. In this study, an environmental model derived from signal-to-noise ratio (SNR) is proposed to enhance the precision and convergence time of positioning in harsh environments. A series of experiments are conducted on weighting and ambiguity-fixed models to evaluate performance. The results indicate that the proposed SNR-dependent environment model could lead to a significant improvement in precision and convergence time; with an obtained root mean squared result on the millimeter level, a convergence time of a few seconds, and utilization which could reach 100%, for continuous and reliable positioning results. These results indicate that the proposed SNR-dependent environment model enhances the performance of GNSS monitoring and early warning to provide continuous and reliable positioning results in real-time.

The Sarez Dam, currently recognized as the world’s highest natural dam, holds immense economic significance, necessitating the reliable monitoring and early detection of potential deformations. This study utilizes the Beidou high-precision deformation monitoring system for the dam. Employing baseline network solutions, precise point positioning, and real-time kinematic positioning, the monitoring data from October 2021 to March 2023 were meticulously processed and comparatively analyzed. The results reveal varied degrees of displacement deformation at all sites, with horizontal deformation towards the lake center and vertical deformation showing subsidence. The three-dimensional vector average displacement is 29.1 mm, with an average monthly rate of 4.3 mm/month, and the maximum deformation is 41.4 mm. The cause of the horizontal deformation towards the lake center may be a slow collapse of the coastal soil and rock towards the lake center. Additionally, the monitoring detected a 7.2-magnitude earthquake on 23 February 2023, 52 km from the dam, causing an average displacement of 22.5 mm towards the south, which is 20 times the monthly deformation rate. In summary, deformation is present within the dam monitoring area, with a relatively stable deformation rate, warranting continued tracking and monitoring. Furthermore, earthquakes significantly impact dam deformation, necessitating heightened attention to the potential for seismic-induced dam damage in the future.

This paper addresses the trajectory tracking control problem of Autonomous Underwater Vehicles (AUVs). A comprehensive mathematical model is first established based on Newtonian mechanics, incorporating both kinematic and dynamic equations. By reasonably neglecting the minor influence of roll motion, a five-degree-of-freedom (5-DOF) underactuated AUV model is derived. Considering the strong nonlinearities, high coupling, and time-varying hydrodynamic parameters typical of underwater environments, a fuzzy adaptive PID controller is proposed. This controller combines the adaptability of fuzzy logic with the structural simplicity and reliability of PID control, making it well-suited to the demanding requirements of AUV motion control. Extensive simulation experiments are conducted to evaluate the controller’s performance under various operating conditions. The results show that the fuzzy adaptive PID controller significantly outperforms conventional PID and standalone fuzzy logic controllers in terms of convergence speed and oscillation suppression. Furthermore, a theoretical stability analysis is provided to ensure that the proposed control system remains stable under time-varying fuzzy gain scheduling, confirming its effectiveness and potential for practical application in underwater vehicle control.

The global navigation satellite system provides real-time and all-weather positioning with high accuracy. Under a good observational environment, short-baseline real-time kinematic (RTK) can provide centimeter-level positioning results. However, RTK without model correction of ionospheric delay can significantly reduce the positioning accuracy, and cannot achieve fast and high-precision positioning when the baseline is too long or heavily occluded. Therefore, we propose a combined RTK/fifth-generation (5G) mobile communication technology positioning model by combining global positioning system-RTK with 5G time-of-arrival observations to improve the positioning accuracy under medium and long baselines. Experimental validation and analysis were conducted based on the measured data of different baseline lengths. The results revealed that the combined RTK/5G positioning model markedly improved the positioning performance in both static and dynamic modes under medium- and long-distance baselines. In particular, the RTK/5G model can also achieve good positioning results in conditions where some satellites are occluded. The combined RTK/5G positioning model is important for achieving high-accuracy, real-time, and continuous positioning in complex environments.

The satellite-induced code bias variation of geostationary satellite orbit satellites and medium earth orbit satellites of the second-generation BeiDou Navigation Satellite System (BDS-2) exceeds 1 m, which severely affects the accuracy and stability of the ambiguity resolution and high-precision positioning. With the development of the third-generation BDS (BDS-3) with a new system design and new technology, analysis of the satellite-induced code variation characteristics of BDS-3 has become increasingly important. At present, many scholars have explored the satellite-induced code bias of BDS-3, but most of them focus on BDS-3 experimental satellites via normal geodetic antenna. Compared to normal geodetic antenna, the 40-m dish antenna from the National Time Service Center can accurately detect satellite-induced code variations with low noise and high gain. Thus, observational data from fifteen BDS-3 medium earth orbit satellites are collected with the B1I/B2b/B3I/B1C/B2a frequency bands on the day of year (DOY) 199–206 in 2019, the PRN numbers of which are C19/C20/C21/C22/C23/C24/C25/C26/C27/C28/C30/C32/C33 /C35/C37, via the 40 m dish antenna to analyze the code bias variation characteristics. The results show that the obvious satellite-induced elevation‑dependent code bias variations exist in the B1I/B2b/B3I/B1C/B2a frequency bands of C28, compared with other satellites. Similarly, the multipath (MP) combination of B3I has an obvious elevation‑dependent variation within a range of 0.1 m for C21/C24/C27/C28/C37 and elevation‑dependent variation of the B2a and B2b frequency bands also exists in most satellites with a range of 0.1 m. However, the MP combination values of some satellites are asymmetric with respect to elevation, which is different from BDS-2 satellites and especially obvious for BDS-3 satellites B1I and BIC frequency bands with elevation‑dependent variations of 0.2 m, indicating that the code bias variation is not uniquely related to elevation, especially for the B1I/BIC frequency bands. What’s more, the satellite-induced code bias variation of the BDS-3 satellites is greatly reduced compared with that of the BDS-2 satellites. In addition, the similar code bias variation appears at the Xia1 station with a normal geodetic antenna of B1I/B1C/B3I/B2a/B2b of C21, B3I/B2a/B2b of C24 and B2b of C28 among B1I/B1C/B3I/B2a/B2b of C21/C24/C27/C28/C37. The influence of the BDS-3 satellite-induced elevation‑dependent code bias on precision positioning and ambiguity fixing is worth further study using different antennas or receivers.