Real-time Kinematic Research Articles

Inherent Limitations of Smartphone GNSS Positioning and Effective Methods to Increase the Accuracy Utilizing Dual-Frequency Measurements

Xiaomi Mi8 with a Broadcom BCM47755 chip, an Android smartphone that supports multi-constellation (GPS, GLONASS, Galileo, BeiDou, and QZSS) and dual-frequency (L1/E1 and L5/E5), was launched in May 2018. Unlike previously released smartphones, it was technically expected to provide robust precise positioning with a fast ambiguity resolution, which led many researchers to be overly optimistic about the applicability of high-accuracy techniques such as real-time kinematic (RTK) systems and precise point positioning (PPP) of smartphones. The global navigation satellite system (GNSS) raw measurement quality of Android smartphones is, however, inherently far lower than that of general GNSS receivers due to their structure, which accordingly makes it difficult for them to be realized. Considering inherent limitations of smartphones such as low-quality antenna, frequent cycle slips, and the duty cycle, a practical strategy including L5 measurements, pseudo-range corrections for L5, and a weighting method is proposed in this paper. The results show that the proposed methods of L5 differential GNSS (DGNSS) and Doppler-based filtering can guarantee a positioning accuracy of 1.75 m horizontally and 4.56 m vertically in an Android device, which is comparable to the performance of commercial low-cost receivers.

İnsansız Hava Araçlarının Orman Yolu Projelerinde Kullanımı

Road networks are accepted as a criterion showing the level of development of countries. Undoubtedly, the role of highways in facilitating human life is quite important. However, road routes involve high cost land surveying studies that can pass through areas with various land use types and cover.For forest road routes to be built in forest areas, points representing the land surface can be obtained by various measurement methods (remote sensing, photogrammetry and terrestrial measurement techniques). Depending on the land structure and cover, difficulties are encountered in the determination of spatial points with terrestrial measurement techniques. In this study, as an alternative to the terrestrial measurement technique, 341 m long forest road excavation and filling calculations were carried out with the help of Unmanned Aerial Vehicle (UAV) photogrammetry. Photo pairs taken from different heights (50 m, 75 m and 100 m) with real-time kinematics (RTK) GPS UAV were processed with Agisoft to produce a point cloud. The point cloud data obtained by digital photogrammetry and land measurement methods were carried out in NetCAD environment for the excavation and filling calculations for the same road route. Between the two methods, in the 50 m, 75 m and 100 m measurements of the UAV obtained by ground measurement; In the calculation of the UAV 50m measurement amount, 0.27% in the total excavation amount and 1.08% difference in the total filling amount, 2.51% in the total excavation amount and 5.22% in the total filling amount in the calculation of the UAV 75 m measurement amount, and the total difference in the UAV 100m measurement amount in the calculation of the UAV 50m measurement amount. A difference of 3.13% in the amount of excavation and 2.53% in the total amount of filling was determined. These results show that UAV photogrammetry is very effective in forest road projects and in calculating the amount of earthwork volume in mountainous terrain.

Landmark-Based Scale Estimation and Correction of Visual Inertial Odometry for VTOL UAVs in a GPS-Denied Environment.

With the rapid development of technology, unmanned aerial vehicles (UAVs) have become more popular and are applied in many areas. However, there are some environments where the Global Positioning System (GPS) is unavailable or has the problem of GPS signal outages, such as indoor and bridge inspections. Visual inertial odometry (VIO) is a popular research solution for non-GPS navigation. However, VIO has problems of scale errors and long-term drift. This study proposes a method to correct the position errors of VIO without the help of GPS information for vertical takeoff and landing (VTOL) UAVs. In the initial process, artificial landmarks are utilized to improve the positioning results of VIO by the known landmark information. The position of the UAV is estimated by VIO. Then, the accurate position is estimated by the extended Kalman filter (EKF) with the known landmark, which is used to obtain the scale correction using the least squares method. The Inertial Measurement Unit (IMU) data are used for integration in the time-update process. The EKF can be updated with two measurements. One is the visual odometry (VO) estimated directly by a landmark. The other is the VIO with scale correction. When the landmark is detected during takeoff phase, or the UAV is returning to the takeoff location during landing phase, the trajectory estimated by the landmark is used to update the scale correction. At the beginning of the experiments, preliminary verification was conducted on the ground. A self-developed UAV equipped with a visual-inertial sensor to collect data and a high-precision real time kinematic (RTK) to verify trajectory are applied to flight tests. The experimental results show that the method proposed in this research effectively solves the problems of scale and the long-term drift of VIO.

Assessment of the Steering Precision of a UAV along the Flight Profiles Using a GNSS RTK Receiver

Photogrammetric surveys are increasingly being carried out using Unmanned Aerial Vehicles (UAV). Steering drones along the flight profiles is one of the main factors that determines the quality of the compiled photogrammetric products. The aim of this article is to present a methodology for performing and processing measurements, which are used in order to determine the accuracy of steering any drone along flight profiles. The study used a drone equipped with a Global Navigation Satellite System (GNSS) Real Time Kinematic (RTK) receiver. The measurements were performed on two routes which comprised parallel profiles distant from each other by 10 m and 20 m. The study was conducted under favourable meteorological conditions (windless and sunny weather) at three speeds (10 km/h, 20 km/h and 30 km/h). The cross track error (XTE), which is the distance between a UAV’s position and the flight profile, calculated transversely to the course, was adopted as the accuracy measure of steering a UAV along the flight profiles. Based on the results obtained, it must be concluded that the values of XTE measures for two representative routes are very similar and are not determined by the flight speed. The XTE68 measure (p = 0.68) ranged from 0.39 m to 1.00 m, while the XTE95 measure (p = 0.95) ranged from 0.60 m to 1.22 m. Moreover, analyses demonstrated that the statistical distribution of the XTE measure was most similar to the gamma and Weibull (3P) distributions.

Application and Accuracy of Unmanned Aerial Survey Imagery after Salvage Logging in Different Terrain Conditions

The accuracy of the positioning of the data collected by remote sensing platforms is of great importance in forest and wildlife surveys, salvage logging, soil disturbances after felling operations, fire risk management and many other forestry-based research. The significance of bark beetles in silver fir and Norway spruce stands is an essential factor that can affect the increase in biomass quantity and the reduction of its quality. Due to an Ips typographus (L.) outbreaks in the central part of Croatia from 2016 to 2021, salvage logging was performed in an area of 11,940 ha, with terrain slopes varying from 0 to 172.83%. Two plots of similar sizes (<5 ha) and different terrain conditions (flat vs. sloped terrain) were chosen and were measured in June 2022. Measurements included a total station, a real-time kinematic (RTK) GNSS (Global Navigation Satellite System) terrestrial receiver and an unmanned aerial system (UAS) in order to determine the accuracy of a digital terrain model (DEM) generated by a photogrammetric UAS. In total, 175 checkpoints were marked in the field. Four different GCP (Ground Control Point) classes (5, 10, 15 and 20) were used to compare validation points acquired from the original point clouds, imagery and orthophotos to the reference positions. This study showed that, in terms of a forest area recognition after conducted salvage logging, the use of 10 GCPs for terrain evaluation is necessary even in small areas below 5 ha and regardless of terrain slope.

Clothoid-Based Lane-Level High-Definition Maps: Unifying Sensing and Control Models

Autonomous vehicles rely on lane-level high-definition (HD) maps for self-localization and trajectory planning. Current mapping, however, relies on simple line models, while clothoid curves have unexplored potential. Clothoids, well known in road design, are often chosen to model the vehicle trajectory in planning and control systems as they describe the road with higher fidelity. For this reason, we propose two vision-based pipelines for generating lane-level HD maps using clothoid models. The first pipeline performs mapping with known poses, requiring precise real-time kinematics GPS (RTK GPS) measurements; the second copes with noisy localizations, solving the simultaneous localization and mapping (SLAM) problem. Both pipelines rely on a line detection algorithm to identify each line marking and perform a graph-based optimization to estimate the map.

Mapping inland water bathymetry with Ground Penetrating Radar (GPR) on board Unmanned Aerial Systems (UASs)

Bathymetry of inland water bodies is essential for river maintenance and flood risk management. Traditionally, in shallow water bodies, bathymetry is retrieved by operators wading through the water body with Real Time Kinematic (RTK) Global Navigation Satellite System (GNSS), whilst in deeper waters, it is retrieved with sonar instruments on manned or unmanned boats. In the past, researchers have documented the use of Ground Penetrating Radar (GPR) on boats (i.e. water-coupled GPR) for monitoring the bathymetry of frozen and non-frozen water bodies. Furthermore, GPR has been used on helicopters for monitoring ice and snow thickness. However, deployment of GPR on board Unmanned Aerial Systems (UASs) in non-frozen inland water bodies with electric conductivity higher than 100 μS/cm (as is common in most inland waterbodies in non-polar regions) is unexplored. In this paper, we document the possibility to use drone-borne and water-coupled GPR in several cross-sections located in three different waterbodies (1 lake and 2 rivers) in Denmark. These waterbodies had different bed sediment materials and vegetation conditions, an electric conductivity varying from 200 to 340 μS/cm and depths up to 2.5 m. Drone-borne GPR showed accuracy similar to water-coupled GPR when compared to RTK GNSS ground-truth measurements, with a Mean Absolute Error (MAE) of approx. 8 cm. The only limitations of drone-borne GPR were i) more restrictive minimum depth requirement (typically 0.8–1.1 m for drone-borne GPR, while 0.3–0.4 m for water-coupled GPR) ii) requirement to fly the GPR antenna at altitudes of approx. 0.5 m above the water surface to avoid high spreading losses and strong surface clutter events hiding the signal. Finally, GPR measurements were benchmarked against traditional sonar measurements, showing that GPR measurements significantly outperform sonar measurements in waterbodies with medium or high density of aquatic vegetation.

Research on autonomous driving technology for a robot vehicle in mountainous farmland using the Quasi-Zenith Satellite System

The centimeter-level augmentation service (CLAS) provided by Michibiki (also known as the Quasi-Zenith Satellite System (QZSS)) can be utilized as a navigation sensor for a robot vehicle in orchards, which are often located in mountainous areas with steep slopes. Buildings, windbreaks, and the inclination of the antenna affected the CLAS less than they did the virtual reference station real-time kinematic (VRS-RTK) method, which is one of the most common navigation sensors for autonomous driving in agriculture. The time to first fix (TTFF) of the CLAS was 60 s earlier near buildings and 90 s earlier in case of a tilted antenna compared to that of the VRS-RTK. Moreover, the CLAS does not depend on an internet signal such as that provided for mobile broadband, since it uses augmentation information from the QZSS. A positioning test in a real vineyard, where grapevines are trained over vertical trellises, revealed that the CLAS could acquire FIX solutions constantly, whereas the VRS-RTK could not because of weak internet signals. The accuracy of the CLAS was less than 6.4 cm for a 95% confidence interval at static positioning and less than 3 cm root mean square (RMS) at dynamic positioning. A robot vehicle navigated by the CLAS autonomously traveled two paths, including a turning maneuver, with less than 9 cm RMS and less than 20 cm MAX. The results showed that the CLAS enabled the robot vehicle to work autonomously without any collisions in an actual vineyard.

GNSS RTK/UWB/DBA Fusion Positioning Method and Its Performance Evaluation

As a significant space–time infrastructure, the Global Navigation Satellite System (GNSS) provides high-precision positioning, navigation, and timing (PNT) information to users all over the world. However, GNSS real-time kinematic (RTK) mobile receiver signal attenuation is obvious in complex environments such as under trees, urban canyons, and indoors, among others, and it is incapable of meeting the demand of multi-level mass users for indoor and outdoor seamless positioning applications. The goal of this study was to address the limitations and vulnerabilities of the GNSS RTK positioning above-mentioned. First, we propose a GNSS RTK/UWB/DBA fusion positioning model and provide detailed algorithm steps for various types of observations. The performance of the GNSS RTK/UWB/DBA fusion positioning under various occlusion environments is then thoroughly evaluated using static and dynamic cart experiments. The experiment results show that as the elevation mask angle increases, the number of available GNSS satellites decreases and the ambiguity resolution success rate decreases; in comparison to GNSS RTK, the proposed GNSS RTK/UWB/DBA fusion positioning model can significantly improve the spatial geometry distribution of observations, reduce the position dilution of precision (PDOP) value, and improve the ambiguity resolution success rate. At an elevation mask angle of 50 degrees, GNSS RTK/UWB/DBA combination positioning can improve the ambiguity resolution success rate by 20% to 60%, and a positioning error less than 5 cm by 20% to 50%. It also indicates that the GNSS RTK/UWB/DBA fusion positioning model has higher positioning accuracy and can effectively improve the availability and reliability of GNSS RTK in a local harsh environment.

GCPs-Free Photogrammetry for Estimating Tree Height and Crown Diameter in Arizona Cypress Plantation Using UAV-Mounted GNSS RTK

One of the main challenges of using unmanned aerial vehicles (UAVs) in forest data acquisition is the implementation of Ground Control Points (GCPs) as a mandatory step, which is sometimes impossible for inaccessible areas or within canopy closures. This study aimed to test the accuracy of a UAV-mounted GNSS RTK (real-time kinematic) system for calculating tree height and crown height without any GCPs. The study was conducted on a Cupressus arizonica (Greene., Arizona cypress) plantation on the Razi University Campus in Kermanshah, Iran. Arizona cypress is commonly planted as an ornamental tree. As it can tolerate harsh conditions, this species is highly appropriate for afforestation and reforestation projects. A total of 107 trees were subjected to field-measured dendrometric measurements (height and crown diameter). UAV data acquisition was performed at three altitudes of 25, 50, and 100 m using a local network RTK system (NRTK). The crown height model (CHM), derived from a digital surface model (DSM), was used to estimate tree height, and an inverse watershed segmentation (IWS) algorithm was used to estimate crown diameter. The results indicated that the means of tree height obtained from field measurements and UAV estimation were not significantly different, except for the mean values calculated at 100 m flight altitude. Additionally, the means of crown diameter reported from field measurements and UAV estimation at all flight altitudes were not statistically different. Root mean square error (RMSE < 11%) indicated a reliable estimation at all the flight altitudes for trees height and crown diameter. According to the findings of this study, it was concluded that UAV-RTK imagery can be considered a promising solution, but more work is needed before concluding its effectiveness in inaccessible areas.

Production of orthophoto map using mobile photogrammetry and comparative assessment of cost and accuracy with satellite imagery for corridor mapping: a case study in Manesar, Haryana, India

ABSTRACT The study aims to find a low-cost alternate technology to get imagery, using mobile platform, and produce digital orthophoto for corridor mapping, with a higher degree of accuracy and which can reduce the lag time of acquisition of data. The present study uses digital single-lens reflex cameras, mounted on a mobile vehicle, and acquisition of data in the video format rather than still photographs, as traditionally used in mobile mapping systems. The videos are used to create a set of images and orthophotos. A widespread ground control points were recorded in the study area, using the global navigation satellite system receiver, which measured the control points in real-time kinematic mode. Generation of digital orthophoto has been completed using the captured mobile imagery and ground control point. Furthermore, procurement of satellite imagery and aerial triangulation using ground control points have been done. While comparing the planimetric accuracy of orthophoto against satellite imagery using the ground control points, the achieved root mean square error value of produced orthophoto is 0.171 m in X axis and 0.205 m in Y axis. However, for Cartosat -1 satellite imagery, the RMSE value for X is 1.22 m and for Y is 1.98 m. This research proposes the alternate low-cost mobile mapping method to capture the imagery for orthophoto production. The cost of orthophoto production from mobile image was found 77% cheaper than the orthophoto cost from fresh/latest satellite imagery procurement, while the overall production was 70% cost-effective than the orthophoto maps made from archived imagery.

Performance tests of geodetic receivers with tilt sensors in obstructed environments using the NRTK GNSS technique

Abstract The Department of Lands (DOL), Thailand, has adopted the Network-based Real-Time Kinematic (NRTK) Global Navigation Satellite System (GNSS) surveying technique using a Virtual Reference Station (VRS) to support cadastral surveys since 2011. Determining accurate coordinates of parcel boundary markers at building corners or near fences and walls is difficult because a GNSS range pole cannot be leveled with a circular bubble. This study aims to evaluate the performance of the receivers equipped with tilt sensors for horizontal and vertical positioning. Two types of tilt sensors used for evaluation were a magnetometer and micro-electro-mechanical system (MEMS) and an inertial measurement unit (IMU). Conducting the NRTK GNSS surveying tests was based on the pole tilt angles of 0°, 15°, 25°, 35°, and 45° from a plumb line in controlled and obstructed environments. The IMU-based tilt sensor had more advantage of accurately positioning over the MEMS sensor. The results showed that using the IMU, better than 4 cm horizontal positioning accuracy was achievable when the pole was tilted by 15° or less under non-multipath and open-sky conditions. The vertical accuracy was of a few centimeter levels and least sensitive to tilt angles using either type of sensor. However, none of the sensors precisely compensated for pole tilt in strong-multipath and complex environments, causing increased horizontal errors in decimeter levels.

Performance Evaluation of GNSS Position Augmentation Methods for Autonomous Vehicles in Urban Environments.

Global Navigation Satellite Systems provide autonomous vehicles with precise position information through the process of position augmentation. This paper presents a series of performance tests aimed to compare the position accuracy of augmentation techniques such as classical Differential Global Navigation Satellite System, Real-time Kinematic and Real-time eXtended. The aim is to understand the limitations and choose the best position augmentation technique in order to obtain accurate, trustworthy position estimates of a vehicle in urban environments. The tests are performed in and around the German cities of Wuppertal and Duesseldorf, using a vehicle fitted with the navigation system POS-LV 220, developed by Applanix Corporation. In order to evaluate the real-time performance of position augmentation techniques in a highly challenging environment, a total of four test regions are selected. The four test regions are characterized mainly by uneven terrain with tall buildings around the University of Wuppertal, flat terrain with roads of varying width in the city centre of Wuppertal and Duesseldorf and flat terrain in a tunnel section located in the city of Wuppertal. The performances of the different position augmentation are compared using a Root Mean Square (RMS) error estimate obtained as an output from the Applanix system. Furthermore, a High-Definition map of the environment is used for the purpose of model validation, which justifies the use of RMS error estimate as an evaluation metric for the performance analysis tests. According to the performance tests carried out as per the conditions specified in this paper, the Real-time eXtended (RTX) position augmentation method enables to obtain a more robust position information of the vehicle than Real-time Kinematic (RTK) method, with a typical accuracy of a few centimeter in an urban environment.

Quasi-4-dimension ionospheric modeling and its application in PPP

Ionospheric delay modeling is not only important for Global Navigation Satellite System (GNSS) based space weather study and monitoring, but also an efficient tool to speed up the convergence time of Precise Point Positioning (PPP). In this study, a novel model, denoted as Quasi-4-Dimension Ionospheric Modeling (Q4DIM) is proposed for wide-area high precision ionospheric delay correction. In Q4DIM, the Line Of Sight (LOS) ionospheric delays from a GNSS station network are divided into different clusters according to not only the location of latitude and longitude, but also satellite elevation and azimuth. Both Global Ionosphere Map (GIM) and Slant Ionospheric Delay (SID) models that are traditionally used for wide-area and regional ionospheric delay modeling, respectively, can be regarded as the special cases of Q4DIM by defining proper grids in latitude, longitude, elevation, and azimuth. Thus, Q4DIM presents a resilient model that is capable for both wide-area coverage and high precision. Four different sets of clusters are defined to illustrate the properties of Q4DIM based on 200 EUREF Permanent Network (EPN) stations. The results indicate that Q4DIM is compatible with the GIM products. Moreover, it is proved that by inducting the elevation and azimuth angle dependent residuals, the precision of the 2-dimensional GIM-like model, i.e., Q4DIM 2-Dimensional (Q4DIM-2D), is improved from around 1.5 Total Electron Content Units (TECU) to better than 0.5 TECU. In addition, treating Q4DIM as a 4-dimensional matrix in latitude, longitude, elevation, and azimuth, whose sparsity is less than 5%, can result in its feasibility in a bandwidth-sensitive applications, e.g., satellite-based Precising Point Positioning Real-Time Kinematic (PPP-RTK) service. Finally, the advantages of Q4DIM in PPP over the 2-dimensional models are demonstrated with the one month's data from 30 EPN stations in both high solar activity year 2014 and low solar activity year 2020.

A method of real-time long-baseline time transfer based on the PPP-RTK

Long-baseline time transfer can nowadays reach rather high frequency stability based on post-processed batch least-squares adjustment using the Precise Point Positioning (PPP) or Integer-PPP (IPPP) methods. For real-time PPP users, time transfer results are degraded due to the filter-based processing mode, and the degraded accuracy of the real-time satellite orbits and clocks compared to the final ones. The Real-Time Kinematic (RTK) time transfer can significantly reduce the satellite-related errors, but has limits on the baseline length similar to the RTK positioning. Also, the delivery of raw observations instead of State-Space Representation (SSR) products could result in pressure on data transfer and difficulties related to latency and prediction. In this study, the PPP-RTK technique, which combines the advantages of the PPP and the RTK methods, is tested for real-time long-baseline time transfer. As an alternative approach to the above two methods, it allows for the time transfer of long baselines, while not relying on external high-sampling and high-precision satellite clocks. By delivering the satellite clocks and satellite phase biases produced within the PPP-RTK regional network, time differences can be estimated between users and the reference network station, with which stable time transfer between users separated by long baselines can be realized. Using dual-frequency GPS and Galileo data, the PPP-RTK time transfer is tested using approximately a thousand-kilometer-scale network in Europe. The time transfer results between two hydrogen masers, i.e., those on the 884 km baseline BRUX-ONSA and the 920 km baseline WTZR-ONSA, are computed. At an averaging time of 105 s, Modified Allan Deviation (MDEV) at the level of sub-10-15 to 10-15 can be reached when processing the user coordinates in the station fixed, static, or kinematic modes. The median clock residuals can converge to 1 ns and 0.3 ns within 2 min and 15 min, respectively, in the kinematic mode, while in the static and fixed modes the convergence times are shorter. With the augmentation of 150 Low Earth Orbit (LEO) satellites having simulated observations, the clock residuals can converge to 1 ns and 0.3 ns within 30 s and 3.5 min, respectively, for all the three estimation modes.

Improving Vehicle Positioning Performance in Urban Environment with Tight Integration of Multi-GNSS PPP-RTK/INS

Global navigation satellite system (GNSS) signals are easily blocked by urban canyons, tree-lined roads, and overpasses in urban environments, making it impossible to ensure continuous and reliable positioning using only GNSS, even with the widely used precise point positioning and real-time kinematic (PPP-RTK). Since the inertial navigation system (INS) and GNSS are complementary, a tightly coupled PPP-RTK/INS model is developed to improve the positioning performance in these GNSS-challenged scenarios, in which the atmospheric corrections are used to achieve a rapid ambiguity resolution and the mechanization results from INS are utilized to assist GNSS preprocessing, re-fixing, and reconvergence. The experiment was conducted using three sets of vehicle-mounted data, and the performance of low-cost receiver and microelectromechanical system (MEMS) inertial measurement unit (IMU) was compared. The result shows that the positioning accuracy of PPP-RTK/INS can reach 2 cm in the horizontal component and 5 cm in the vertical component in the open environment. In the complex urban environment, continuous and reliable positioning can be ensured during GNSS short interruption, ambiguity can be instantaneously re-fixed with the assistance of INS, and decimeter-level positioning accuracy can be achieved. As a result, the horizontal positioning errors of more than 95% of the total epochs were within 20 cm. In addition, average positioning accuracy better than 15 cm and 30 cm in the horizontal and vertical components, respectively, can be obtained using the low-cost receiver and MEMS IMU. Compared with tactical IMU, the improvements in positioning accuracy and the ambiguity fixing rate using the geodetic receiver were more significant.

A trajectory similarity-based method to evaluate GNSS kinematic precise positioning performance with a case study

There is a lack of effective testing methods to evaluate high-precision global navigation satellite system (GNSS) kinematic positioning solutions, such as GNSS real-time kinematic (RTK) or post-processed kinematic (PPK), with centimeter-level accuracy. Current methods either process static GNSS data in kinematic mode to perform a pseudo-kinematic test or use a precise motion table to make a real-kinematic test but within a very limited travel distance. This study proposes a trajectory similarity method by moving a track trolley platform along a railway track, which can match the GNSS positioning trajectory and the pre-surveyed reference track. The GNSS trajectory offsets from the reference track along the cross-track and vertical directions are regarded as GNSS kinematic positioning errors. Lever-arm compensation is applied to achieve millimeter-level accuracy for this evaluation method. A case study was conducted to evaluate the positioning performance of the Global Positioning System/BeiDou Navigation Satellite System (GPS/BDS) PPK using the proposed method. The results indicate that the proposed method can provide a reference trajectory on the order of a few millimeters, which is sufficiently accurate even for PPK positioning performance evaluation and error source tracing in wide regions. In this case, cycle slips as small as 10 cm in the carrier phase measurements can be detected and studied based on the proposed method.

Global Navigation Satellite System Real-Time Kinematic Positioning Framework for Precise Operation of a Swarm of Moving Vehicles.

The global navigation satellite system (GNSS) real-time kinematic (RTK) technique is used to achieve relative positioning centimeter levels among multiple agents on the move. A typical GNSS RTK estimates the relative positions of multiple rover receivers with respect to a single-base receiver. In a fleet of rover GNSS receivers, this approach is inefficient because each rover receiver only uses GNSS measurements of its own and those sent from a single-base receiver. In this study, we propose a novel GNSS RTK framework that facilitates the precise positioning of a swarm of moving vehicles through the GNSS measurements of multiple receivers and broadcasts fixed-integer ambiguities of GNSS carrier phases. The proposed framework not only provides efficient RTK positioning but also reliable performance with a limited number of GNSS satellites in view. Our experimental flight tests with six GNSS receivers showed that the systematic procedure of the proposed framework could maintain lower than 6 cm of 3D RMS positioning errors, whereas the conventional RTK failed to resolve the correct integer ambiguities of double difference carrier phase measurements more than 13% in five out of nine total baselines.

Designing an outdoor machinery monitoring device with integrated real-time kinematic positioning

Accurate positioning ofoutdoor vehicles and machinery is of the top importance inmanagement, tracking, analysis, and control applications. However, most of the current vehicle tracking devices have an error of a few meters to several tens of meters,which is not enough for applications requiring high accuracy. This paper presents the design of an outdoor machinery monitoring device that integrates precise positioning technology of real-time kinematic (RTK). The device uses U-Blox’s Zed F9P module as the core to perform the high accuracy positioning function. Thanks to the integration of RTK positioning technology, the device can monitor the location of machinery outdoors with centimeter-level accuracy.

Experimental Study of Accuracy of High-Rate GNSS in Context of Structural Health Monitoring

Global Navigation Satellite Systems (GNSS)-based technologies have become an indispensable part of current structural health monitoring (SHM) systems because of the unique capability of the GNSS technologies to provide accurate real-time displacement information. GNSS equipment with a data sampling rate of up to about 20 Hz has been widely used for this purpose. High-rate GNSS systems (typically up to about 100 Hz) offer additional advantages in structural health monitoring as some highly dynamic civil structures, such as some bridges, require high-rate monitoring data to capture the dynamic behaviors. However, the performance of high-rate GNSS positioning in the context of structural health monitoring is not entirely known, as studies on structural monitoring with high-rate GNSS positioning are very limited, especially considering that some of the satellite systems just reached their full constellations very recently. We carried out a series of experiments with the help of a shaking table to assess the SHM performance of a set of 100 Hz GNSS equipment and three commonly used GNSS positioning techniques, PPP (precise point positioning), PPP-AR (precise point positioning with ambiguity resolution), and RTK (real-time kinematic). We found that the standard deviations of the 100 Hz GNSS displacement solutions derived from PPP, PPP-AR, and RTK techniques were 5.5 mm, 3.6 mm, and 0.8 mm, respectively, when the antenna was in quasi-static motion, and about 9.2 mm, 6.2 mm, and 3.5 mm, respectively, when the antenna was in vibration (up to about 0.7 Hz), under typical urban observational conditions in Hong Kong. We also found that the higher a sampling rate is, the lower the accuracy of a measured displacement series is. On average, the 10 Hz and 100 Hz results are 5.5% and 10.3%, respectively, noisier than the 1 Hz results.