Network Real-time Kinematic Systems Research Articles

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.

EVALUATION OF CAMERA POSITIONS AND GROUND POINTS QUALITY IN A GNSS-NRTK BASED UAV SURVEY: PRELIMINARY RESULTS FROM A PRACTICAL TEST IN MORPHOLOGICAL VERY COMPLEX AREAS

Abstract. Open pit mines localized in high mountains are probably one of the most complex environments for Structure-From-Motion (SfM) based photogrammetry. The case study presented in this paper refers to the realization of a detailed topographic mapping in the Torano marble basin (Apuan Alps, Italy) which needed, after decades of excavation activity, a new topographic survey.Given the requested very high resolution, the time constraints and safety-related problems, a photogrammetric approach by a fixedwing Unmanned Aerial Vehicle (UAV) was chosen to carry out thesurvey of the basin. In addition, given the morphological complexity of the area, characterized by extreme steep slopes more than hundreds of meters high, and the necessity to minimize the fieldwork without sacrificing the work quality, an UAV equipped with a L1/L2 Network Real Time Kinematic (NRTK) Global Navigation Satellite System (GNSS) was used.The scope of this work is to compare the accuracy of UAV derived 3D photogrammetric models realized with different approaches: by using traditional Ground Control Points (GCPs), by using the on-board Network Real Time Kinematic system for camera position detection, and a mix of both. At the end, we tested the quality of the models to verify the reachable levels of accuracy.

A New Algorithm for High-Integrity Detection and Compensation of Dual-Frequency Cycle Slip under Severe Ionospheric Storm Conditions.

Many strategies for treating dual-frequency cycle slip, which can seriously affect the performance of a carrier-phase-based positioning system, have been studied over the years. However, the legacy method using the Melbourne-Wübbena (MW) combination and ionosphere combination is vulnerable to pseudorange multipath effects and high ionospheric storms. In this paper, we propose a robust algorithm to detect and repair dual-frequency cycle slip for the network-based real-time kinematic (RTK) system which generates high-precision corrections for users. Two independent and complementary carrier-phase combinations, called the ionospheric negative and positive combinations in this paper, are employed for avoiding insensitive pairs. In addition, they are treated as second-order time differences to reduce the impact of ionospheric delay even under severe ionospheric storm. We verified that the actual error distributions of these monitoring values can be sufficiently bounded by the normal Gaussian distribution. Consequently, we demonstrated that the proposed method ensures high-integrity performance with a maximum probability of missed detection of 7.5 × 10−9 under a desired false-alarm probability of 10−5. Furthermore, we introduce a LAMBDA-based cycle slip compensation method, which has a failure rate of 1.4 × 10−8. Through an algorithm verification test using data collected under a severe ionospheric storm, we confirmed that artificially inserted cycle slips are successfully detected and compensated for. Thus, the proposed method is confirmed to be effective for handling dual-frequency cycle slips of the network RTK system.

A Self-Organizing Spatial Clustering Approach to Support Large-Scale Network RTK Systems.

The network real-time kinematic (RTK) technique can provide centimeter-level real time positioning solutions and play a key role in geo-spatial infrastructure. With ever-increasing popularity, network RTK systems will face issues in the support of large numbers of concurrent users. In the past, high-precision positioning services were oriented towards professionals and only supported a few concurrent users. Currently, precise positioning provides a spatial foundation for artificial intelligence (AI), and countless smart devices (autonomous cars, unmanned aerial-vehicles (UAVs), robotic equipment, etc.) require precise positioning services. Therefore, the development of approaches to support large-scale network RTK systems is urgent. In this study, we proposed a self-organizing spatial clustering (SOSC) approach which automatically clusters online users to reduce the computational load on the network RTK system server side. The experimental results indicate that both the SOSC algorithm and the grid algorithm can reduce the computational load efficiently, while the SOSC algorithm gives a more elastic and adaptive clustering solution with different datasets. The SOSC algorithm determines the cluster number and the mean distance to cluster center (MDTCC) according to the data set, while the grid approaches are all predefined. The side-effects of clustering algorithms on the user side are analyzed with real global navigation satellite system (GNSS) data sets. The experimental results indicate that 10 km can be safely used as the cluster radius threshold for the SOSC algorithm without significantly reducing the positioning precision and reliability on the user side.

Reliability Analysis of Network Real-Time Kinematic

The multistate reliability theory was applied to the network real-time kinematic (NRTK) data processing chain, where the qualities of the network corrections, baseline residuals, and the associated variance-covariance matrices are considered as the system state vectors. The state vectors have direct influence on the rover receiver position accuracy. The penalized honored stochastic averaged standard deviation (PHSASD) is used to map the NRTK sensitive data, represented by the states vectors to different levels of performance. The study shows that the improvement is possible by identification of critical components in the NRTK system and implementation of some parallelism that makes the system more robust.

Three-step Algorithm for Rapid Ambiguity Resolution between Reference Stations within Network RTK

The correct ambiguity resolution between reference stations is the core issue of the whole Network Real-Time Kinematic (RTK) technology. Aimed at long fixed time and low reliability of the low elevation angle satellite ambiguity resolution during the initialisation of the Network RTK system, a three-step algorithm is proposed in this paper. Firstly, the double difference wide-lane ambiguities are fixed on the basis of the Melbourne-Wubbena (MW) method. Secondly, the double difference L1 carrier phase ambiguities of the high elevation angle satellites are fixed rapidly based on the ionosphere-free combination model. Thirdly, the corresponding ambiguities of the satellites with low elevation angles are solved with restrictions from the double difference tropospheric information, which is obtained from observations of the high elevation angle satellites. Based on this algorithm, an overall scheme of the ambiguity resolution during the initialisation process of the Network RTK system is designed. Results from Global Positioning System (GPS)/Globalnaya Navigatsionnaya Sputnikovaya Sistema (GLONASS) data demonstrate that the three-step algorithm can reduce the ill-posed problems of the observation model effectively. Moreover, the speed and accuracy performances of the ambiguity resolution for the low elevation angle satellites using the proposed algorithm are better than those of the conventional method.

Algorithms for Sparse Network-based RTK GPS Positioning and Performance Assessment

The average inter-station distances in most established network Real Time Kinematic (RTK) systems are constrained to around 50 km. A sparse network RTK system with an average inter-station distance of up to 300 km would have many appealing advantages over a conventional one, including a significant reduction in the development and maintenance costs. The first part of this paper introduces the key approaches for sparse network RTK positioning technology. These include long-range reference baseline ambiguity resolution and real-time kinematic ambiguity resolution for the rover receivers. The proposed method for long-range kinematic ambiguity resolution can overcome the network weaknesses through three procedures: application of the interpolated corrections from the sparse network only to wide-lane combination; searching the ambiguities of wide-lane combination; and searching L1 ambiguities with wide-lane combination and ionosphere-free observables. To test these techniques, a network including ten reference stations was created from the Ordnance Survey's Network (OS NetTM) that covers the whole territory of the United Kingdom (UK). The average baseline length of this sparse network is about 300 km. To assess the positioning performance, nine rover stations situated inside and outside the network were also selected from the OS Net™. Finally, the accuracy of interpolated corrections, the positioning accuracy and the initialization time required for precise positioning were estimated and analysed. From the observed performance of each rover receiver, and the accuracy of interpolated network corrections, it can be concluded that it is feasible to use a sparse reference station network with an average inter-station distance up to 300 km for achieving similar performance to traditional network RTK positioning. The proposed approach can provide more cost-efficient use of network RTK (NRTK) positioning for engineering and environmental applications that are currently being delivered by traditional network RTK positioning technology.

An Examination of Network RTK GPS Services in Great Britain

As of March 2009, network real-time kinematic (RTK) GPS surveying is available in Great Britain with the aid of two commercial service providers, Leica's “SmartNet” and Trimble's “VRS Now”, both of which rely largely on the Ordnance Survey's “OS Net” network of around 120 continuously operating reference stations. With the aim of testing the performance of Network RTK under both ideal and less-ideal conditions (greater distances and elevation differences from the nearest reference stations, proximity to the edges of OS Net, and increased susceptibility to ocean tide loading effects), we have tested the positional accuracy of both commercial Network RTK systems by comparison with precise coordinates determined using the Bernese scientific GPS processing software, at six representative locations spanning England and Wales. We find that the coordinate quality measures provided by the Network RTK solutions are overall representative of the actual coordinate accuracy, which is typically 10-20 mm in plan and 15-35 mm in height, and can be successfully used to identify outliers. Positional accuracy tends to be poorest outside of the bounds of OS Net and at greater elevation differences from nearby reference stations. Averaging of coordinates over two short windows separated by 20-45 minutes can be used to achieve moderate improvements in coordinate accuracy without the need for single long occupations of sites.

The Compact Network RTK Method: An Effective Solution to Reduce GNSS Temporal and Spatial Decorrelation Error

This paper proposes a method that combines compact real-time kinematic (RTK) and reference station (RS) networking techniques, and shows that this approach can reduce both the temporal and spatial decorrelation error. The compact RTK method compatibility with all the conventional network RTK systems, i.e., Master-Auxiliary Concept (MAC), Virtual Reference Stations (VRS), and Flächen-Korrektur Parameter (FKP), is examined theoretically in this paper. To prove that the compact RTK approach is not only valid, but also helpful to the network RTK system, a field test was held using one hour of Receiver Independent Exchange Format (RINEX) data logged every second from Continuously Operating Reference Stations (CORS). No matter which network RTK method is applied, the Compact Network RTK approach resolves the ambiguity of the carrier phase in 10–40 s and determines position with 6–7 cm horizontal and 7–8 cm vertical error (95%) in a 100 by 100 km region. Moreover, the Compact Network RTK approach enables network RTK service providers to reduce the data-link bandwidth for correction messages to 5–700 bps (bit/s) down from several thousand bps, currently 9600 bps of GPRS/GSM, without a severe degradation of accuracy.

QoS-Aware Reference Station Placement for Regional Network RTK

Network RTK (Real-Time Kinematic) is a technology that is based on GPS (Global Positioning System) or more gener-ally on GNSS (Global Navigation Satellite System) measurements to achieve centimeter-level accuracy positioning in real-time. Reference station placement is an important problem in the design and deployment of network RTK systems as it directly affects the quality of the positioning service and the cost of the network RTK systems. This paper identifies a new reference station placement for network RTK, namely QoS-aware regional network RTK reference station placement problem, and proposes an algorithm for the new reference station placement problem. The algorithm can always produce a reference station placement solution that completely covers the region of network RTK.