Search Results (228)

Multiple-reference-station-based real-time kinematics (MR-RTK) is an advanced RTK technique that leverages global navigation satellite system (GNSS) measurements from multiple reference stations and their known baselines. This study investigates the fault detection capabilities of MR-RTK by employing additional measurements from continuously operating reference stations (CORSs) to evaluate the probability of missed detection. The proposed method was validated using test data from a ground rover and a few CORSs within a 10 km radius. The test results show that the missed detection probability decreased by up to 55.0% as the number of reference stations increased up to four. Full article

This article presents the design, implementation, and validation of a Remotely Piloted Safety Cone (RPSC), an autonomous robotic system developed to enhance safety and operational efficiency in road maintenance. The RPSC addresses challenges associated with road works, including workers’ exposure to traffic hazards and inefficiencies of traditional traffic cones, such as manual placement and retrieval, limited visibility in low-light conditions, and inability to adapt to dynamic changes in work zones. In contrast, the RPSC offers autonomous mobility, advanced visual signalling, and real-time communication capabilities, significantly improving safety and operational flexibility during maintenance tasks. The RPSC integrates sensor fusion, combining Global Navigation Satellite System (GNSS) with Real-Time Kinematic (RTK) for precise positioning, Inertial Measurement Unit (IMU) and encoders for accurate odometry, and obstacle detection sensors within an optimised navigation framework using Robot Operating System (ROS2) and Micro Air Vehicle Link (MAVLink) protocols. Complying with European regulations, the RPSC ensures structural integrity, visibility, stability, and regulatory compliance. Safety features include emergency stop capabilities, visual alarms, autonomous safety routines, and edge computing for rapid responsiveness. Field tests validated positioning accuracy below 30 cm, route deviations under 15 cm, and obstacle detection up to 4 m, significantly improved by Kalman filtering, aligning with digitalisation, sustainability, and occupational risk prevention objectives. Full article

With the availability of multi-frequency, multi-constellation global navigation satellite system (GNSS) modules, precise transportation applications have become attainable. For transportation applications, GNSS geodetic-grade receivers can achieve an accuracy of a few centimeters to a few decimeters through differential, precise point positioning (PPP), real-time kinematic (RTK), and PPP-RTK solutions in both post-processing and real-time modes; however, these receivers are costly. Therefore, this research aims to assess the accuracy of a cost-effective multi-GNSS real-time PPP solution for transportation applications. For this purpose, the U-blox ZED-F9P module is utilized to collect dual-frequency multi-GNSS observations through a moving vehicle in a suburban area in New Aswan City, Egypt; thereafter, datasets involving different multi-GNSS combination scenarios are processed, including GPS, GPS/GLONASS, GPS/Galileo, and GPS/GLONASS/Galileo, using both RT-PPP and RTK solutions. For the RT-PPP solution, the satellite clock and orbit correction products from Bundesamt für Kartographie und Geodäsie (BKG), Centre National d’Etudes Spatiales (CNES), and the GNSS research center of Wuhan University (WHU) are applied to account for the real-time mode. Moreover, GNSS datasets from two geodetic-grade Trimble R4s receivers are collected; hence, the datasets are processed using the traditional kinematic differential solution to provide a reference solution. The results indicate that this cost-effective multi-GNSS RT-PPP solution can attain positioning accuracy within 1–3 dm, and is thus suitable for a variety of transportation applications, including intelligent transportation system (ITS), self-driving cars, and automobile navigation applications. Full article

Accurate localization of buried water pipelines in rural areas is crucial for maintenance and leak management but is often hindered by outdated maps and the limitations of traditional geophysical methods. This study aimed to develop and validate a multi-source remote-sensing workflow, integrating UAV (unmanned aerial vehicle)-borne near-infrared (NIR) surveys, multi-temporal Sentinel-2 imagery, and historical Google Earth orthophotos to precisely map pipeline locations and establish a surface baseline for future monitoring. Each dataset was processed within a unified least-squares framework to delineate pipeline axes from surface anomalies (vegetation stress, soil discoloration, and proxies) and rigorously quantify positional uncertainty, with findings validated against RTK-GNSS (Real-Time Kinematic—Global Navigation Satellite System) surveys of an excavated trench. The combined approach yielded sub-meter accuracy (±0.3 m) with UAV data, meter-scale precision (≈±1 m) with Google Earth, and precision up to several meters (±13.0 m) with Sentinel-2, significantly improving upon inaccurate legacy maps (up to a 300 m divergence) and successfully guiding excavation to locate a pipeline segment. The methodology demonstrated seasonal variability in detection capabilities, with optimal UAV-based identification occurring during early-vegetation growth phases (NDVI, Normalized Difference Vegetation Index ≈ 0.30–0.45) and post-harvest periods. A Sentinel-2 analysis of 221 cloud-free scenes revealed persistent soil discoloration patterns spanning 15–30 m in width, while Google Earth historical imagery provided crucial bridging data with intermediate spatial and temporal resolution. Ground-truth validation confirmed the pipeline location within 0.4 m of the Google Earth-derived position. This integrated, cost-effective workflow provides a transferable methodology for enhanced pipeline mapping and establishes a vital baseline of surface signatures, enabling more effective future monitoring and proactive maintenance to detect leaks or structural failures. This methodology is particularly valuable for water utility companies, municipal infrastructure managers, consulting engineers specializing in buried utilities, and remote-sensing practitioners working in pipeline detection and monitoring applications. Full article

This study focused on the monitoring of a bridge using the global navigation satellite system real-time kinematic (GNSS-RTK) sensor. An improved hybrid denoising method was developed to enhance the GNSS-RTK’s accuracy. The improved hybrid denoising method consists of the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), the detrended fluctuation analysis (DFA), and an improved wavelet threshold denoising method. The stability experiment demonstrated the superiority of the improved wavelet threshold denoising method in reducing the noise of the GNSS-RTK. A noisy simulation signal was created to assess the performance of the proposed method. Compared to the ICEEMDAN method and the CEEMDAN-WT method, the proposed method achieves lower RMSE and higher SNR. The signal obtained by the proposed method is similar to the original signal. Then, GNSS-RTK was used to monitor a bridge in maintenance and rehabilitation construction. The bridge monitoring experiment lasted for four hours. (Considering the space limitation of the article, only representative 600 s data is displayed in the paper.) The bridge is located in Tianjin, China. The original displacement ranges are −14.9~19.3 in the north–south direction; −26.9~24.7 in the east–west direction; and −46.7~52.3 in the vertical direction. The displacement ranges processed by the proposed method are −12.3~17.2 in the north–south direction; −24.6~24.1 in the east–west direction; and −46.7~51.1 in the vertical direction. The proposed method processed fewer displacements than the initial monitoring displacements. It indicates the proposed method reduces noise significantly when monitoring the bridge based on the GNSS-RTK sensor. The average sixth-order frequency from PSD is 1.0043 Hz. The difference between the PSD and FEA is only 0.99%. The sixth-order frequency from the PSD is similar to that from the FEA. The lower modes’ natural frequencies from the PSD are smaller than those from the FEA. It illustrates the fact that, during the repair process, the missing load-bearing rods made the bridge less stiff and strong. The smaller natural frequencies of the bridge, the complex construction environment, the diversity of workers’ operations, and some unforeseen circumstances occurring in the construction all bring risks to the safety of the bridge. We should pay more attention to the dynamic monitoring of the bridge during construction in order to understand the structural status in time to prevent accidents. Full article

Ensuring Global Navigation Satellite System (GNSS) integrity, which provides operational reliability via fault detection, is important for safety-critical applications using high-precision techniques like Precise Point Positioning (PPP) and Real-Time Kinematic (RTK). Ionospheric errors, from atmospheric free electrons, challenge this integrity by introducing variable uncertainties into positioning solutions. This study investigates how ionospheric error modeling spatial resolution impacts protection level (PL) calculations, a metric defining positioning error bounds with high confidence. A comparative evaluation was conducted in low-latitude (Guangdong) and mid-latitude (Shandong) regions, contrasting large-scale with small-scale grid-based ionospheric models from regional GNSS networks. Experimental results show small-scale grids improve characterization of localized ionospheric variability, reducing ionospheric residual standard deviation by approximately 30% and enhancing PL precision. Large-scale grids show limitations, especially in active low-latitude conditions, leading to conservative PLs that reduce system availability and increase missed fault detection risks. A user-side PL computation framework incorporating this high-resolution ionospheric residual uncertainty improved system availability to 94.7% and lowered misleading and hazardous outcomes by over 80%. This research indicates that refined, high-resolution ionospheric modeling improves operational reliability and safety for high-integrity GNSS applications, particularly under diverse and challenging ionospheric conditions. Full article

The use of spherical cameras for mapping purposes is a common application in surveying. Very expensive and high-quality cameras are used for surveying purposes and are supplemented by systems for determining their position. Cheap cameras, in most cases, only complement laser scanners, and the images are then used to color the laser point cloud. This article investigates the use of action cameras in combination with low-cost GNSS (Global Navigation Satellite System) equipment. The research involves the development of a methodology and software for georeferencing spherical images, created by the kinematic method, using GNSS RTK (Real-Time Kinematics) or PPK (Post-Processing Kinematics) coordinates. Testing was carried out in two case studies where the environment surveyed had varying properties. Considering that the images from the low-cost 360 camera are of lower quality, an artificial intelligence tool was used to improve the quality of the images. The point clouds from a low-cost device are compared with more accurate methods. One of them is the SLAM (Simultaneous Localization and Mapping) method with the Faro Orbis device. The results in this work show sufficient accuracy and data quality for mapping purposes. Due to the very low price of the low-cost device used in this work, it is very easy to extend this method to practice. Full article

Global navigation satellite system (GNSS) real-time kinematic (RTK) has been widely applied in landslide monitoring and warning, since it can provide real-time and high-precision three-dimensional deformation information in all weather and all the time. The Kalman filter is often adopted for parameter estimation in GNSS RTK positioning since it can effectively suppress the observational noise and improve the positioning accuracy and reliability. However, the discrepancy between the empirical state model in the Kalman filter and the actual state of the monitoring object could lead to large positioning errors or even the divergence of the Kalman filter. In this contribution, we propose a novel rapid deformation identification and adaptive filtering approach with GNSS time-differenced carrier phase (TDCP) under different scenarios for landslide monitoring. We first present the methodology of the proposed TDCP-based rapid deformation identification and adaptive filtering approach for GNSS RTK positioning. The effectiveness of the proposed approach is then validated with a simulated displacement experiment with a customized three-dimensional displacement platform. The experimental results demonstrate that the proposed approach can accurately and promptly identify the rapid between-epoch deformation of more than approximately 1.5 cm and 3.0 cm for the horizontal and vertical components for the monitoring object under a complex observational environment. Meanwhile, it can effectively suppress the observational noise and thus maintain mm-to-cm-level monitoring accuracy. The proposed approach can provide high-precision and reliable three-dimensional deformation information for GNSS landslide monitoring and early warning. Full article

With the rapid advancement of artificial intelligence, particularly in fields such as autonomous driving, drone delivery, and logistics automation, the demand for high-precision and robust navigation services has become critical. In complex and dynamic urban environments, the navigation capabilities of single-sensor systems struggle to meet the practical requirements of autonomous driving technology. To address this issue, we propose a multi-source fusion navigation algorithm tailored for dynamic urban canyon scenarios, aiming to achieve reliable and continuous state estimation in complex environments. In our proposed method, we utilize independent threads on a graphics processing unit (GPU) to perform real-time detection and removal of dynamic objects in visual images, thereby enhancing the visual accuracy of multi-source fusion navigation in dynamic scenes. To tackle the challenges of significant Global Navigation Satellite System (GNSS) positioning errors and limited satellite availability in urban canyon environments, we introduce a specialized GNSS Real-Time Kinematic (RTK) stochastic model for such settings. The navigation performance of the proposed algorithm was evaluated using public datasets. The results demonstrate that our RTK/INS/Vision integrated navigation algorithm effectively improves both accuracy and availability in dynamic urban canyon environments. Full article

The characterization of dimensional stone deposits is essential for quarry assessment and design. However, uncertainties in mapping and designing pose significant challenges. To address this issue, an innovative approach is initiated to develop a virtual reality model by integrating unmanned aerial vehicle (UAV) photogrammetry for surface modeling and Electric Resistivity Tomography (ERT) for subsurface deposit imaging. This strategy offers a cost-effective, time-efficient, and safer alternative to traditional surveying methods for challenging mountainous terrain. UAV methodology involved data collection using a DJI Mavic 2 Pro (20 MP camera) with 4 K resolution images captured at 221 m altitude and 80 min flight duration. Images were taken with 75% frontal and 70% side overlaps. The Structure from Motion (SfM) processing chain generated high-resolution outputs, including point clouds, Digital Elevation Models (DEMs), Digital Surface Models (DSMs), and orthophotos. To ensure accuracy, five ground control points (GCPs) were established by a Real-Time Kinematic Global Navigation Satellite System (RTK GNSS). An ERT method known as vertical electric sounding (VES) revealed subsurface anomalies like solid rock mass, fractured zones and areas of iron leaching within marble deposits. Three Schlumberger (VES-1, 2, 3) and two parallel Wenner (VES-4, 5) arrays to a depth of 60 m were employed. The resistivity signature acquired by PASI RM1 was analyzed using 1D inversion technique software (ZondP1D). The integrated outputs of photogrammetry and subsurface imaging were used to design an optimized quarry with bench heights of 30 feet and widths of 50 feet, utilizing open-source 3D software (Blender, BIM, and InfraWorks). This integrated approach provides a comprehensive understanding of deposit surface and subsurface characteristics, facilitating optimized and sustainable quarry design and extraction. This research demonstrates the value of an innovative approach in synergistic integration of UAV photogrammetry and ERT, which are often used separately, for enhanced characterization, decision-making and promoting sustainable practices in dimensional stone deposits. Full article

Achieving high-precision spatiotemporal synchronization is crucial for the implementation of virtual coupling (VC) in railway systems. This paper proposes a moving baseline real-time kinematic (MB-RTK) framework to enhance relative positioning accuracy and synchronization robustness between coupled trains. By leveraging global navigation satellite system (GNSS) carrier-phase differential processing and dynamic baseline estimation, MB-RTK effectively mitigates positioning errors caused by GNSS signal degradation, multipath interference, and synchronization latency, ensuring stable and reliable inter-train coordination. The proposed framework was evaluated through comprehensive simulations and field experiments. The results demonstrate that MB-RTK achieves centimeter-level relative positioning accuracy under normal GNSS conditions, maintains tracking errors within 10 m, and typically keeps velocity synchronization deviations within ±0.5 km/h. Furthermore, the RTK status analysis reveals that NARROW_INT provides the highest stability, while continuous RTK corrections are essential to ensure seamless synchronization in dynamic environments. To further enhance synchronization performance, a decentralized distributed synchronization algorithm was introduced, reducing communication overhead and improving real-time responsiveness. The proposed approach exhibits strong resilience to GNSS disruptions, making it well-suited for high-density and autonomous train operations. Overall, this study highlights MB-RTK as a promising solution for VC applications, offering high accuracy, low latency, and strong adaptability in complex railway scenarios. Future research will focus on AI-driven dynamic corrections, integration with complementary localization methods, and large-scale deployment strategies to further optimize the system’s robustness and scalability. Full article

Precise Point Positioning with real-time kinematic (PPP-RTK) technology, which relies on Global Navigation Satellite Systems (GNSS), encounters difficulties in achieving high-precision and rapid convergence during ionospheric active conditions such as those occurring in thunderstorms. Most existing research on PPP-RTK has primarily focused on calm ionospheric conditions, with limited analysis of its performance under ionospheric anomalies. This study analyzes 13-day data collected from 305 Australian stations, encompassing both ionospheric anomalies (from 10 to 13 May 2024) and calm periods. We evaluated the residuals of uncalibrated phase delay (UPD), the accuracy of atmospheric modeling, as well as the positioning accuracy and convergence time of PPP-RTK. The results reveal that during ionospheric anomalies, compared to calm conditions, the accuracy of wide-lane and narrow-lane UPDs decreases by 2.4% and 1.4%, respectively. Meanwhile, the accuracy of estimated ionospheric and tropospheric delays deteriorates by 167.1% and 17.3%, respectively. In terms of PPP-RTK services, for the horizontal component, the convergence times increase by 25.0%, 44.4%, and 55.6% for the GPS-only, GPS + Galileo, and GPS + Galileo + BDS solutions, respectively. For the vertical component, the increases are 56.9%, 81.6%, and 87.2%, respectively. Regarding the positioning accuracies, for the horizontal component, they decline by 5.5%, 7.4%, and 10.4% for the GPS-only, GPS + Galileo, and GPS + Galileo + BDS solutions, respectively. For the vertical component, the declines are 11.8%, 13.0%, and 18.5%, respectively. This indicates that ionospheric anomalies significantly disrupt PPP-RTK services, mainly due to the degradation of ionospheric delay estimates, which directly affects positioning results. Although the ionosphere can lead to significant degradation in positioning performance, the positioning performance can still be substantially improved with an increase in the number of satellites. This study thus offers new insights into the performance of PPP-RTK during ionospheric active conditions. Full article

Nowadays, several smartphones on the market provide multi-frequency multi-constellations GNSS measurements, including carrier phase ones, allowing the achievement of high-accuracy positioning by exploiting Real Time Kinematic (RTK) or Precise Point Positioning (PPP) techniques. This paper will showcase the effectiveness of using smartphone measurements for RTK under different scenarios and for different applications using baselines of different lengths. The impact of the smartphone’s antenna on the solution will also be analysed. The assessment will be performed by evaluating different key performance indicators, including the time to first fix and the horizontal/vertical accuracy. This paper shows that around a 99% fix position can be achieved even using the smartphones’ antennas for the static case under open sky conditions. Moreover, high percentages of fix solutions can also be achieved in kinematic mode by ad hoc tuning of the RTK algorithm. Full article

Coaxial drones have garnered popularity owing to their energy efficiency and compact design. However, the precise navigation of these drones in complex and dynamic flight scenarios is limited by inaccuracies in heading/yaw estimation. Conventional heading estimation methods rely on magnetometers and real-time kinematic Global Navigation Satellite Systems (RTK-GNSS), which directly measure heading angle. However, the small size of microdrones restricts the placement of magnetometers away from magnetic interference and prevents the use of directional antennas. Moreover, single-antenna alignment algorithms are highly susceptible to errors caused by nonlinearity, leading to significant inaccuracies in heading estimation. To address these challenges, this paper proposes a hybrid heading estimation approach that integrates Motion-Adaptive Stabilization with an Angle-Parameterized Extended Kalman Filter (APEKF). This method utilizes low-cost GNSS, a magnetometer, and an Inertial Measurement Unit (IMU). Heading is initialized based on the drone’s static attitude, with an adaptive threshold established during takeoff to account for varying flight conditions. As the drone reaches higher altitudes, heading estimation is further stabilized. GNSS velocity observations enhance estimation accuracy through horizontal maneuvering alignment achieved by incorporating multiple sub-filter techniques and residual-based fusion. In the simulations and onboard experiments in this study, the proposed heading estimation method demonstrated a precision of approximately 1.01° post-takeoff, with the alignment speed enhanced by 43%. Moreover, the method outperformed existing estimation techniques and, owing to its low computational overhead, can serve as a reliable full-stage backup across various drone applications. Full article

As the peak of solar cycle 25 approaches, increased ionospheric and scintillation activity is being observed, which is negatively impacting the quality of GNSS measurements and presenting challenges in the positioning domain. Ionospheric refraction and diffraction introduce delays and distortions to GNSS carrier phase measurements, leading to positioning errors that exceed the anticipated accuracies. These position errors can be a significant concern for users across the world who depend on precise GNSS positioning, such as in agriculture, offshore marine positioning and autonomous automotive positioning. To understand the direct impact on NovAtel receivers and its positioning engines, a comprehensive analysis was conducted. A closer look was taken at what happened in 2023–2024 by characterizing scintillation using the amplitude scintillation index (S4) values in an equatorial region. Additionally, the scintillation effect on the receivers was characterized through the analysis of C/N0, lock breaks, double differences and other indicators. With a substantial amount of data collected at 20° latitude, where high solar activity occurs due to the proximity to the equator, the positioning performance of Real-Time Kinematic (RTK) and Precise Point Positioning (PPP) was analyzed. Full article