Network RTK Research Articles

Performance Evaluation of Real-Time Kinematic Global Navigation Satellite System with Survey-Grade Receivers and Short Observation Times in Forested Areas

The Real-Time Kinematic (RTK) method is currently the most widely used method for positioning using Global Navigation Satellite Systems (GNSSs) due to its accuracy, efficiency and ease of use. In forestry, position is a critical factor for numerous applications, with GNSS currently being the preferred solution for obtaining such data. However, the decreased performance of GNSS observations in challenging environments, such as under the forest canopy, must be considered. This paper analyzes the performance of a survey-grade GNSS receiver under coniferous/deciduous tree cover. Unlike most previous research concerning this topic, the focus here is on employing a methodology that is as close as possible to real working conditions in the field of forestry. To achieve this, short observation times of 30 s were used, with corrections received directly in the field from a Continuously Operating Reference Station (CORS) of the national RTK network in Romania. In total, 84 test points were determined, randomly distributed under the canopy, with reference data collected by topographical surveys using total station equipment. In terms of the overall horizontal accuracy, an RMSE of 2.03 m and MAE of 1.63 m are found. Meanwhile, the overall vertical accuracy is lower, as expected, with an RMSE of 4.85 m and MAE of 4.01 m. The variation in GNSS performance under the different forest compositions was found to be statistically significant, while GNSS-specific factors such as DOP values only influenced the precision and not the accuracy of observations. We established that this methodology offers sufficient accuracy, which is application-dependent, even if the majority of GNSS solutions were code-based, rather than carrier-phase-based, due to strong interference from the vegetation.

A New Precise Point Positioning with Ambiguity Resolution (PPP-AR) Approach for Ground Control Point Positioning for Photogrammetric Generation with Unmanned Aerial Vehicles

Unmanned aerial vehicles (UAVs) are now widely preferred systems that are capable of rapid mapping and generating topographic models with relatively high positional accuracy. Since the integrated GNSS receivers of UAVs do not allow for sufficiently accurate outcomes either horizontally or vertically, a conventional method is to use ground control points (GCPs) to perform bundle block adjustment (BBA) of the outcomes. Since the number of GCPs to be installed limits the process in UAV operations, there is an important research question whether the precise point positioning (PPP) method can be an alternative when the real-time kinematic (RTK), network RTK, and post-process kinematic (PPK) techniques cannot be used to measure GCPs. This study introduces a novel approach using precise point positioning with ambiguity resolution (PPP-AR) for ground control point (GCP) positioning in UAV photogrammetry. For this purpose, the results are evaluated by comparing the horizontal and vertical coordinates obtained from the 24 h GNSS sessions of six calibration pillars in the field and the horizontal length differences obtained by electronic distance measurement (EDM). Bartlett’s test is applied to statistically determine the accuracy of the results. The results indicate that the coordinates obtained from a two-hour PPP-AR session show no significant difference from those acquired in a 30 min session, demonstrating PPP-AR to be a viable alternative for GCP positioning. Therefore, the PPP technique can be used for the BBA of GCPs to be established for UAVs in large-scale map generation. However, the number of GCPs to be selected should be four or more, which should be homogeneously distributed over the study area.

Combined decoupled clock and integer‑estimable models applied to CDMA + FDMA single-difference network RTK

Combined decoupled clock and integer‑estimable models applied to CDMA + FDMA single-difference network RTK

Compact RTK for expanded area (COREA): a new method for carrier-phase-based satellite augmentation system

This study proposes a new concept of carrier-phase-based satellite augmentation system named “Compact Real-time Kinematic for Expanded Area (COREA),” which provides centimeter-level positioning services across nationwide coverage. The proposed system’s architecture is very similar to that of the satellite-based augmentation system (SBAS), a meter-level aviation safety service. While network real-time kinematic and precise-point-positioning-RTK (PPP-RTK) rely on several densely positioned reference stations, COREA provides carrier-phase-based corrections using a few reference stations with a distance of 400–1000 km. Furthermore, the COREA corrections can be transmitted by satellite signals with extremely low-speed data links of 250 bps, similar to SBAS. This study focused on the generation method for satellite code/phase clock (CPC) corrections, which is the most significant part of the system. We analyzed the user performance of the COREA system constructed in the Midwest and South of the United States with six reference stations. Consequently, satellite CPC corrections are resilient to communication failures and highly accurate in identifying user integer ambiguity. The 95% position accuracy is approximately 1.8 cm horizontally and 7.1 cm vertically, with an average convergence time of 1–3 min using only GPS triple-frequency signals. In summary, the COREA system preserves the hardware architecture of the legacy SBAS while providing centimeter-level services with fast convergence times by utilizing extremely low-speed satellite data links across the country.

Research on agricultural monitoring and progressive map creation in the context of ground-air coordination

Abstract By combining network RTK technology, 2D LiDAR, and UAV, this study investigates how to achieve agricultural monitoring effectively. A collaborative agricultural monitoring scheme was designed to accurately and comprehensively gather agricultural information in response to the demand for targeted sequential monitoring at specified agricultural locations. To establish a low-cost and low computational power-dependent 3D map of obstacle point clouds, a progressive 3D mapping scheme based on 2D LiDAR was designed and implemented. The effectiveness of the design was validated through simulation experiments and partly through real-world testing.

High-precision tropospheric correction method for NRTK regions with significant height differences

Abstract In response to the issue of poor network real-time kinematic (NRTK) service performance in regions with significant height differences, an improved tropospheric height correction (ITHC) method is proposed. Precise point positioning (PPP) is employed to compute the troposphere delay at base stations. Subsequently, a tropospheric vertical profile fitting model (TVPFM) is established for the vertical reduction of the troposphere in regions with significant height differences. In this case, the tropospheric errors introduced by the height differences between the base and rover stations can be calculated. Finally, the tropospheric error can be corrected during the generation of virtual observations, ensuring high-accuracy positioning of NRTK rovers. With the troposphere delay computed based on the PPP approach, datum errors introduced by inaccurate tropospheric correction methods are mitigated. To reduce the dependence of the troposphere delay on height, ECMWF reanalysis v5 (ERA5) data are employed to fit the TVPFM. Experimental analysis demonstrates that the troposphere exhibits distinct vertical variation characteristics, allowing for its segmentation into three layers. Consequently, a piecewise TVPFM is established. Observations obtained from the continuously operating reference stations network located in Yunnan, China, are utilized for validation. The selected stations exhibit a maximum height difference of approximately 2 km. The experimental results exhibit a notable enhancement in correction accuracy with the ITHC in comparison to conventional correction methodologies. Specifically, the ambiguity fixing rate demonstrates a noteworthy improvement of 13.3%, accompanied by a substantial increase in positioning accuracy by 51.4%.

Fast and Reliable Network RTK Positioning Based on Multi-Frequency Sequential Ambiguity Resolution under Significant Atmospheric Biases

The positioning performance of the Global Navigation Satellite System (GNSS) network real-time kinematic (NRTK) depends on regional atmospheric error modeling. Under normal atmospheric conditions, NRTK positioning provides high accuracy and rapid initialization. However, fluctuations in atmospheric conditions can lead to poor atmospheric error modeling, resulting in significant atmospheric biases that affect the positioning accuracy, initialization speed, and reliability of NRTK positioning. Consequently, this decreases the efficiency of NRTK operations. In response to these challenges, this paper proposes a fast and reliable NRTK positioning method based on sequential ambiguity resolution (SAR) of multi-frequency combined observations. This method processes observations from extra-wide-lane (EWL), wide-lane (WL), and narrow-lane (NL) measurements; performs sequential AR using the LAMBDA algorithm; and subsequently constrains other parameters using fixed ambiguities. Ultimately, this method achieves high precision, rapid initialization, and reliable positioning. Experimental analysis was conducted using Continuous Operating Reference Station (CORS) data, with baseline lengths ranging from 88 km to 110 km. The results showed that the proposed algorithm offers positioning accuracy comparable to conventional algorithms in conventional NRTK positioning and has higher fixed rate and positioning accuracy in single-epoch positioning. On two datasets, the proposed algorithm demonstrated over 30% improvement in time to first fix (TTFF) compared to conventional algorithms. It provides higher precision in suboptimal positioning solutions when conventional NRTK algorithms fail to achieve fixed solutions during the initialization phase. These experiments highlight the advantages of the proposed algorithm in terms of initialization speed and positioning reliability.

Improving LiDAR height precision in urban environment: Low-cost GNSS ranging prototype for post-mission airborne laser scanning enhancement

Although Light Detection and Ranging (LiDAR) technology is currently one of the most efficient methods for acquiring high-density point cloud, there are still challenges in terms of data reliability. In particular, the accuracy assessment of LiDAR data, especially in the height component, is one of the main issues in this context. This study introduces a rapid and cost-effective platform to improve the accuracy and precision of LiDAR data by integrating high-density GNSS-Ranging measurements with LiDAR data. The platform offers the capability to rapidly collect a significant number of network real time kinematic (NRTK) points with centimetric precision. A continuous correction surface is proposed to integrate the platform and LiDAR data, resulting in improved accuracy for all ground-class LiDAR data. Evaluation using GNSS benchmarks and NRTK checkpoints showed a significant reduction in LiDAR height errors after applying the correction surface. The root mean squares error (RMSE) decreased from 18.5 cm to 8.2 cm when compared to GNSS benchmarks and from 17.4 cm to 5.3 cm for approximately 1000 NRTK control points. The results indicate that collecting a large number of high-density GNSS ground targets and applying a correction surface to LiDAR height data significantly enhance the accuracy and precision of the LiDAR extracted products.

An overall adjustment method for relative corrections of master reference stations in the BDS/GNSS network RTK system

We here address problems of nonunique paths and poor fault tolerance in the traditional shortest path transfer method and propose an overall adjustment method of relative corrections of master reference stations in BDS/GNSS Network RTK systems. Our method comprehensively considers the vector relationship of baseline error corrections, the baseline closure error of Delaunay triangulation and the interpolation relationship between stations to realize the one-time generation, obtaining all relative error corrections of the master reference station in a network RTK system. The test results showed that our method can achieve a success rate of more than 95% and an incorrect rate of less than 0.01%. The error corrections, generated by the two methods, are verified and analysed by the positioning accuracy of the rover. The results show that the positioning accuracy of the method in this paper is improved by about 17% over the shortest path transfer method.

New Concept of Smart UAS-GCP: A Tool for Precise Positioning in Remote-Sensing Applications

Today, ground control points (GCPs) represent indispensable tools for products’ georeferencing in all the techniques concerning remote sensing (RS), particularly in monitoring activities from unmanned aircraft system (UAS) platforms. This work introduces an innovative tool, smart GCPs, which combines different georeferencing procedures, offering a range of advantages. It can serve three fundamental purposes concurrently: (1) as a drone takeoff platform; (2) as a base station, allowing the acquisition of raw global navigation satellite system (GNSS) data for post-processed kinematic (PPK) surveys or by providing real-time GNSS corrections for precision positioning; (3) as a rover in the network real-time kinematic (NRTK) mode, establishing its position in real time with centimetric precision. The prototype has undergone testing in a dedicated study area, yielding good results for all three geodetic correction techniques: PPK, RTK, and GCP, achieving centimeter-level accuracy. Nowadays, this versatile prototype represents a unique external instrument, which is also easily transportable and able to connect to the GNSS RING network, obtaining real-time positioning corrections for a wide range of applications that require precise positioning. This capability is essential for environmental applications that require a multitemporal UAS-based study. When the real-time RING data are accessible to the scientific community operating in RS surveying, this work could be a helpful guide for researchers approaching such investigations.

Research and Design of Network RTK High-precision Positioning and Computer Vision Service Platform Based on Beidou

Research and Design of Network RTK High-precision Positioning and Computer Vision Service Platform Based on Beidou

Studying the Repeatability of Measurements Obtained via Network Real-Time Kinematic Positioning at Different Times of the Day

The network real-time kinematic (NRTK) positioning technique is currently used in numerous applications. The aim of this study was to better understand the process of obtaining accurate positions by statistically evaluating the significance of differences between repeated measurements for a single point at different times of the day (morning, noon, and evening) using the Virtual Reference Station (VRS), Flächen Korrektur Parameter (FKP), and Master Auxiliary Concept (MAC) correction methods. An analysis of variance (ANOVA) was used to this effect. Further analysis was carried out to determine the accuracy and precision of the coordinate differences obtained via a static GNSS (global navigation satellite system) and by averaging the repeated measurements. It was determined that the accuracy and precision of the vertical component of the coordinates were lower than that of the horizontal component. The FKP correction method yielded the best results. It was observed that the accuracy and precision of the measurements taken at noon were the lowest. The ANOVA showed that the differences between repeated measurements were statistically significant and that there were outlier measurements. The results of this study are important for NRTK users to be able to statistically evaluate different measurement configurations and obtain positions with the desired accuracy and precision.

Designing and Testing an IoT Low-Cost PPP-RTK Augmented GNSS Location Device.

Nowadays, the availability of affordable multi-constellation multi-frequency receivers has broadened access to accurate positioning. The abundance of satellite signals coupled with the implementation of ground- and satellite-based correction services has unlocked the potential for achieving real-time centimetre-level positioning with low-cost instrumentation. Most of the current and future applications cannot exploit well-consolidated satellite positioning techniques such as Network Real Time Kinematic (RTK) and Precise Point Positioning (PPP); the former is inapplicable for large user bases due to the necessity of a two-way communication link between the user and the NRTK service provider, while the latter necessitates long convergence times that are not in keeping with kinematic application. In this context, the hybrid PPP-RTK technique has emerged as a potential solution to meet the demand for real-time, low-cost, accurate, and precise positioning. This paper presents an Internet of Things (IoT) GNSS device developed with low-cost hardware; it leverages a commercial PPP-RTK correction service which delivers corrections via IP. The main target is to obtain both horizontal and vertical decimetre-level accuracies in urban kinematic tests, along with other requisites such as solution availability and the provision of connection ports for interfacing an IoT network. A vehicle-borne kinematic test has been conducted to evaluate the device performance. The results show that (i) the IoT device can deliver horizontal and vertical positioning solutions at decimetre-level accuracy with the targeted solution availability, and (ii) the provided IoT ports are feasible for gathering the position solutions over an internet connection.

Research on Reliable Long-Baseline NRTK Positioning Method Considering Ionospheric Residual Interpolation Uncertainty

In the past few decades, network real-time kinematic (NRTK) positioning technology has developed rapidly. Generally, in the continuously operating reference stations (CORS) network, within a moderate baseline length, e.g., 80–100 km, atmospheric delay can be effectively processed through regional modeling and, thus, can support almost instantaneous centimeter-level NRTK positioning. However, in long-baseline CORS networks, especially during the active period of the ionosphere, ionospheric delays cannot be fully eliminated through modeling, leading to decreased NRTK positioning accuracy. To address this issue, this study proposes a long-baseline NRTK positioning method considering ionospheric residual interpolation uncertainty (IRIU). The method utilizes the ionospheric residual interpolation standard deviation (IRISTD) calculated during atmospheric delay modeling, then fits an IRISTD-related stochastic model through the fitting of the absolute values of the ionospheric delay modeling residuals and IRISTD. Finally, based on the ionosphere-weighted model, the IRISTD processed by the stochastic model is used to constrain the ionospheric pseudo-observations. This method achieves good comprehensive performance in handling ionospheric delay and model strength, and the advantage is validated through experiments using CORS data with baseline lengths ranging from 54 km to 106 km in western China and from 84 km to 180 km in AUSCORS data. Quantitative results demonstrate that, across the three sets of experiments, the proposed ionosphere-weighted model achieves an average increase in the fixed rate of 16.9% compared to the ionosphere-fixed model and 25.6% compared to the ionosphere-float model. In terms of positioning accuracy, the proposed model yields average improvements of 67.4%, 76.4%, and 66.0% in the N/E/U directions, respectively, compared to the ionosphere-fixed model, and average improvements of 21.0%, 32.0%, and 24.4%, respectively, compared to the ionosphere-float model. Overall, the proposed method can achieve better NRTK positioning performance in situations where ionospheric delay modeling is inaccurate, such as long baselines and ionospheric activity.

The efficiency of single base and network RTK for Structural Health Monitoring

The efficiency of single base and network RTK for Structural Health Monitoring

Predicting C/N0 as a Key Parameter for Network RTK Integrity Prediction in Urban Environments

Autonomuous transportation systems require navigation performance with a high level of integrity. As Global Navigation Satellite System (GNSS) real-time kinematic (RTK) solutions are needed to ensure lane level accuracy of the whole system, these solutions should be trustworthy, which is often not the case in urban environments. Thus, the prediction of integrity for specific routes or trajectories is of interest. The carrier-to-noise density ratio (C/N0) reported by the GNSS receiver offers important insights into the signal quality, the carrier phase availability and subsequently the RTK solution integrity. The ultimate goal of this research is to investigate the predictability of the GNSS signal strength. Using a ray-tracing algorithm together with known satellite positions and 3D building models, not only the satellite visibility but also the GNSS signal propagation conditions at waypoints along an intended route are computed. Including antenna gain, free-space propagation as well as reflection and diffraction at surfaces and vegetation, the predicted C/N0 is compared to that recorded by an Septentrio Altus receiver during an experiment in an urban environment in Hannover. Although the actual gain pattern of the receiving antenna was unknown, good agreements were found with small offsets between measured and predicted C/N0.

Comparison of MyRTKnet Performance with Various Real-Time Corrections Based on Different Time

Virtual Reference Station (VRS), Master-Auxiliary Corrections (MAX), Individualised Master-Auxiliary Corrections (IMAX), Nearest Base, and Network D-GNSS are among the Network Real-Time Kinematic (NRTK) techniques supported by the Malaysia Real-Time Kinematic GNSS Network (MyRTKnet) in providing network-based solutions to users. However, different network corrections have different limits due to different characters, thus offering a variety of position accuracy. Therefore, this study evaluated the accuracy of real-time corrections, VRS, MAX, IMAX, D-GNSS, and Nearest Base, for the coordinates at two different times, morning and evening. The study was conducted at two different times to make it easier for users to choose a suitable and quality time to conduct observations. This research was implemented on the pillars at the calibration site of Politeknik Sultan Haji Ahmad Shah (POLISAS) in Kuantan, Pahang. The coordinates in the pillar become a benchmark to differentiate with real-time correction coordinates. The result of that difference can be used to analyse the level of accuracy for real-time corrections. The study’s findings show that the real-time correction accuracy of the VRS type is the most stable and has the highest accuracy. Nearest Base and MAX corrections also give relatively good accuracy and can be improved by increasing observation time and depending on the area. IMAX produces inconsistent results with relatively low accuracy, but some techniques can be applied to obtain good accuracy. D-GNSS type corrections give inconsistent results and low position accuracy as it utilises code measurement only. The research concludes that the best correction is VRS. The Nearest Base and MAX produce acceptable accuracy and can be safely chosen over IMAX and D-GNSS.

An Efficient BDS-3 Long-Range Undifferenced Network RTK Positioning Algorithm

In 2020, the BeiDou-3 global navigation satellite system (BDS-3) was officially completed and put into service. Currently, network real-time kinematic (RTK) technology is considered the main means through which to improve the positioning accuracy of the BeiDou navigation satellite system (BDS). This paper proposes a long-range undifferenced network RTK (URTK) algorithm, based on multi-frequency observation data of the BDS. First, the multi-frequency phase integer ambiguity resolution (AR) model considering atmospheric error parameters is designed, and the multi-frequency phase integer ambiguity of the long-range BDS reference station is determined. Then, the undifferenced integer ambiguity of each reference station is obtained, using linear variation based on the accurately determined phase integer ambiguity between reference stations, and the undifferenced observation error of each reference station is calculated. Considering the weakening spatial correlation of the observation errors between long-range stations, undifferenced classification error corrections of a reference station network are separated, according to different error characteristics. Finally, the inverse distance weighting method is employed to calculate the classification undifferenced error correction of the rover station. The rover station corrects the observation error through applying the undifferenced error correction to achieve high-precision positioning. The measured data of a long-range continuous operation reference station (CORS) network are selected for an experiment. The results show that the proposed algorithm can quickly and accurately realize the resolution of the BDS integer ambiguity of a reference station network and establish an undifferenced area error correction model in order to achieve accurate classification of undifferenced error correction values for a rover station. In China, the BDS-3 is superior to the global positioning system (GPS) in terms of the satellite number, position dilution of precision (PDOP) value, AR success rate, stability, and convergence time. The results show that the AR success rate, stability, and convergence time increase with the operational frequency, and the BDS-3 can achieve centimeter-level positioning of single-system rover stations without relying on the GPS.

A field method to estimate the uncertainty of RTK measurements

The expected accuracies obtainable with Network Real-Time Kinematic (NRTK) measurements are of interest to surveyors working on construction projects. This study introduces an NRTK-based free stationing method called RUFRIS (Real Time Updated Free Station) which is independent from physically marked points. Integration of total station distance and direction observations with NRTK measurements enables uncertainty estimation of both total station and surveyed NRTK points. In Sweden, NRTK is conducted using the national network of permanent reference stations with different densifications (10, 35, 70 km). This paper investigates the applicability of the RUFRIS-method to estimate the uncertainty of NRTK measurements in the field.

Image Mapping Accuracy Evaluation Using UAV with Standalone, Differential (RTK), and PPP GNSS Positioning Techniques in an Abandoned Mine Site.

Global navigation satellite systems (GNSSs) provide a common positioning method that utilizes satellite signals to determine the spatial location of a receiver. However, there are several error factors in standalone GNSS positioning due to instrumental, procedural, and environmental factors that arise during the signal transmission process, and the final positioning error can be up to several meters or greater in length. Thus, real-time kinematic (RTK) correction and post-mission precise point positioning (PPP) processing technologies are proposed to improve accuracy and accomplish precise position measurements. To evaluate the geolocation accuracy of mosaicked UAV images of an abandoned mine site, we compared each orthomosaic image and digital elevation model obtained using standalone GNSS positioning, differential (RTK) GNSS positioning, and post-mission PPP processing techniques. In the three types of error evaluation measure (i.e., relative camera location error, ground control points-based absolute image mapping error, and volumetric difference of mine tailings), we found that the RTK GNSS positioning method obtained the best performance in terms of the relative camera location error and the absolute image mapping error evaluations, and the PPP post-processing correction effectively reduced the error (69.5% of the average total relative camera location error and 59.3% of the average total absolute image mapping error) relative to the standalone GNSS positioning method. Although differential (RTK) GNSS positioning is widely used in positioning applications that require very high accuracy, post-mission PPP processing can also be used in various fields in which it is either not feasible to operate expensive equipment to receive RTK GNSS signals or network RTK services are unavailable.