Special Issue "Integrated Applications of Real-Time GNSS Precise Positioning Services"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".

Deadline for manuscript submissions: 31 March 2022.

Special Issue Editors

Prof. Dr. Xiaolin Meng
E-Mail Website
Guest Editor
Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, 100 Pingleyuan, Chaoyang District, Beijing 100124, China
Interests: global navigation satellite system (GNSS); integrated algorithms and solutions for precise positioning; structural health monitoring; intelligent mobility; connected and autonomous vehicles; precision agriculture and livestock farming, digital innovation
Special Issues and Collections in MDPI journals
Prof. Dr. Weiping Jiang
E-Mail Website
Guest Editor
GNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan 430079, China
Interests: satellite geodesy; satellite altimetry; global navigation satellite system (GNSS); BDS precise positioning; deformation monitoring; time series analysis; terrestrial reference frame
Special Issues and Collections in MDPI journals
Prof. Dr. Jian Wang
E-Mail
Guest Editor
School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing, China
Interests: satellite geodesy; global navigation satellite system; autonomous navigation; self-driving; indoor and outdoor seamless positioning; deformation monitoring; sensor integration
Dr. Craig M. Hancock
E-Mail Website
Guest Editor
School of Architecture, Building and Civil Engineering, Loughborough University, Loughborough LE11 3TU, UK
Interests: GNSS; structural health monitoring; ionosphere; laser scanning
Dr. Zhansheng Liu
E-Mail Website
Guest Editor
The Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing University of Technology, Beijing, China
Interests: BIM; digital twin; intelligent construction; prestressed steel structure; health monitoring

Special Issue Information

Dear Colleagues,

Recent advancements in GNSS technologies and hardware, including improvements in the quality, robustness and quick convergence of real-time PPP algorithms and the advent of the IGS Real-Time-Service (RTS), provide exciting opportunities for present and future applications of GNSS. Over the past decades, there has been a growing demand for precise, real-time positioning and timing services in a variety of different fields including structural health monitoring, intelligent transport systems and services, autonomous vehicle navigation, maritime applications, railway infrastructure monitoring, geohazards warning systems, deep-sea and space explorations and many more.

This Special Issue of Remote Sensing aims to provide a platform for researchers to publish innovative work that pushes the boundaries of the utilization of real-time GNSS in a variety of applications. For instance, integration of precise GNSS positioning with BIM, digital twinning, artificial intelligence, Cloud and Edge Computing and other modern information technologies can be applied in intelligent infrastructure construction, intelligent operation and maintenance, safety risk control, geological disaster monitoring and so on. Potential topics include, but are not limited to, the following:

  • GNSS Precise Positioning Applications in Geodesy
  • Precise Non-linear Motion Modelling of GNSS Reference Stations and Their Physical Mechanisms
  • Aided Real-time GNSS Precise Positioning Services and Sensor Fusion in Challenging Environments
  • Identification of GNSS Error Sources and Mitigation Mechanisms
  • GNSS Augmentation Systems and Integrity Monitoring
  • Real-time GNSS Precise Positioning Services with Smartphones
  • Low-Cost High Performance Real-time GNSS Positioning for Geohazard Monitoring of Volcano, Earthquake, Subsidence and Landslide
  • Integrated Applications of Real-time GNSS Precise Positioning Services, High-definition Mapping and 5G for Connected and Autonomous Vehicles
  • GNSS Precise Positioning Service for Integrated Applications of BIM and Digital Twin in Intelligent Construction, Operation and Maintenance of Large Infrastructure
  • GNSS Precise Positioning Services for Emerging Scientific, Engineering, Environmental and Mass-market Applications

Prof. Dr. Xiaolin Meng
Prof. Dr. Weiping Jiang
Prof. Dr. Jian Wang
Dr. Craig M. Hancock
Dr. Zhansheng Liu
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • GNSS
  • precise positioning
  • autonomous systems
  • sensor integration
  • structural health monitoring
  • geohazard monitoring
  • BIM
  • digital twinning
  • intelligent mobility
  • advanced algorithms

Published Papers (7 papers)

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Research

Article
Performance of Single-Epoch EWL/WL/NL Ambiguity-Fixed Precise Point Positioning with Regional Atmosphere Modelling
Remote Sens. 2021, 13(18), 3758; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13183758 - 19 Sep 2021
Viewed by 306
Abstract
Precise point positioning (PPP) with ambiguity resolution (AR) can improve positioning accuracy and reliability. The narrow-lane (NL) AR solution can reach centimeter-level accuracy but there is a certain initialization time. In contrast, extra-wide-lane (EWL) or wide-lane (WL) ambiguity can be fixed instantaneously. However, [...] Read more.
Precise point positioning (PPP) with ambiguity resolution (AR) can improve positioning accuracy and reliability. The narrow-lane (NL) AR solution can reach centimeter-level accuracy but there is a certain initialization time. In contrast, extra-wide-lane (EWL) or wide-lane (WL) ambiguity can be fixed instantaneously. However, due to the limited correction accuracy of the empirical atmospheric model, the positioning accuracy is only a few decimeters. In order to further improve the real-time performance of PPP while ensuring accuracy, we developed a multi-system multi-frequency uncombined PPP single-epoch EWL/WL/NL AR method with regional atmosphere modelling. In the proposed method, the precise atmosphere, including zenith wet-troposphere delay (ZWD) and the slant ionosphere, is extracted through multi-frequency stepwise AR, which then is both interpolated and broadcast to users. By adding regional atmosphere constraints, users can achieve single-epoch PPP AR with centimeter-level accuracy. To verify the algorithm, four sets of reference networks with different inter-station distances are used for experiments. With atmosphere constraints, the accuracy of the single-epoch WL solution can be improved from the decimeter level to a few centimeters, with an improvement of more than 90%, and the epoch fix rate can also be improved to varying degrees, especially for the dual-frequency case. Due to the enlarged noise of the EWL combination, its accuracy is at the decimeter level, while the accuracy of the WL/NL solution can reach several centimeters. However, reliable NL ambiguity-fixing tightly relies on atmosphere constraints with sufficiently high accuracy. When the modelling of the atmosphere correction is not accurate enough, the NL AR performance is degraded, although this situation can be improved to a certain extent through the multi-GNSS combination. In contrast, in this case, the WL ambiguity can be successfully fixed and can support the precise positioning with an accuracy of several centimeters. Full article
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Article
Pass-by-Pass Ambiguity Resolution in Single GPS Receiver PPP Using Observations for Two Sequential Days: An Exploratory Study
Remote Sens. 2021, 13(18), 3728; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13183728 - 17 Sep 2021
Viewed by 389
Abstract
“Pass-by-pass” or “track-to-track” ambiguity resolution removes Global Navigation Satellite System (GNSS) satellite hardware delays between adjacent undifferenced (UD) ambiguities, which is often applied in precise orbit determination (POD) for Low Earth Orbit (LEO) satellites to improve the accuracy of orbits. In this study, [...] Read more.
“Pass-by-pass” or “track-to-track” ambiguity resolution removes Global Navigation Satellite System (GNSS) satellite hardware delays between adjacent undifferenced (UD) ambiguities, which is often applied in precise orbit determination (POD) for Low Earth Orbit (LEO) satellites to improve the accuracy of orbits. In this study, we carried out an exploratory study to use the “pass-by-pass” ambiguity resolution by differencing the undifferenced ambiguity candidates for two adjacent passes in sidereal days for a single Global Positioning System (GPS) receiver static Precise Point Positioning (PPP). Using the GPS observations from 132 globally distributed reference stations of International GPS Service (IGS), we find that 99.08% wide-lane (WL) and 97.83% narrow-lane (NL) double-difference ambiguities formed by the “pass-by-pass” method for all stations can be fixed to their nearest integers within absolute fractional residuals of 0.2 cycles. These proportions are higher than the corresponding values of network solution with multiple receivers with 97.39% and 91.20%, respectively. About 97% to 98% of ambiguities can be fixed finally on average. The comparison of the estimated station coordinates with the IGS weekly solutions reveals that the Root Mean Square (RMS) in East and North directions are 2-4 mm and is about 6 mm in the Up direction. For hourly data, it is found that the mean positioning accuracy improvement can achieve to about 10% after ambiguity resolution. From a dam deformation monitoring application, it shows that the fixing rate of WL and NL ambiguity can be closed to 100% and higher than 90%, respectively. The time series generated by PPP are also in agreement with the short baseline solutions. Full article
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Article
Modal Parameters Identification of Bridge Structures from GNSS Data Using the Improved Empirical Wavelet Transform
Remote Sens. 2021, 13(17), 3375; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13173375 - 25 Aug 2021
Viewed by 350
Abstract
It is difficult to accurately identify the dynamic deformation of bridges from Global Navigation Satellite System (GNSS) due to the influence of the multipath effect and random errors, etc. To solve this problem, an improved empirical wavelet transform (EWT)-based procedure was proposed to [...] Read more.
It is difficult to accurately identify the dynamic deformation of bridges from Global Navigation Satellite System (GNSS) due to the influence of the multipath effect and random errors, etc. To solve this problem, an improved empirical wavelet transform (EWT)-based procedure was proposed to denoise GNSS data and identify the modal parameters of bridge structures. Firstly, the Yule–Walker algorithm-based auto-power spectrum and Fourier spectrum were jointly adopted to segment the frequency bands of structural dynamic response data. Secondly, the improved EWT algorithm was used to decompose and reconstruct the dynamic response data according to a correlation coefficient-based criterion. Finally, Natural Excitation Technique (NExT) and Hilbert Transform (HT) were applied to identify the modal parameters of structures from the decomposed efficient components. Two groups of simulation data were used to validate the feasibility and reliability of the proposed method, which consisted of the vibration responses of a four-storey steel frame model, and the acceleration response data of a suspension bridge. Moreover, field experiments were carried out on the Wilford suspension bridge in Nottingham, UK, with GNSS and an accelerometer. The fundamental frequency (1.6707 Hz), the damping ratio (0.82%), as well as the maximum dynamic displacements (10.10 mm) of the Wilford suspension bridge were detected by using this proposed method from the GNSS measurements, which were consistent with the accelerometer results. In conclusion, the analysis revealed that the improved EWT-based method was capable of accurately identifying the low-order, closely spaced modal parameters of bridge structures under operational conditions. Full article
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Article
A New Multi-Scale Sliding Window LSTM Framework (MSSW-LSTM): A Case Study for GNSS Time-Series Prediction
Remote Sens. 2021, 13(16), 3328; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13163328 - 23 Aug 2021
Viewed by 373
Abstract
GNSS time-series prediction plays an important role in the monitoring of crustal plate movement, and dam or bridge deformation, and the maintenance of global or regional coordinate frames. Deep learning is a state-of-the-art approach for extracting high-level abstract features from big data without [...] Read more.
GNSS time-series prediction plays an important role in the monitoring of crustal plate movement, and dam or bridge deformation, and the maintenance of global or regional coordinate frames. Deep learning is a state-of-the-art approach for extracting high-level abstract features from big data without any prior knowledge. Moreover, long short-term memory (LSTM) networks are a form of recurrent neural networks that have significant potential for processing time series. In this study, a novel prediction framework was proposed by combining a multi-scale sliding window (MSSW) with LSTM. Specifically, MSSW was applied for data preprocessing to effectively extract the feature relationship at different scales and simultaneously mine the deep characteristics of the dataset. Then, multiple LSTM neural networks were used to predict and obtain the final result by weighting. To verify the performance of MSSW-LSTM, 1000 daily solutions of the XJSS station in the Up component were selected for prediction experiments. Compared with the traditional LSTM method, our results of three groups of controlled experiments showed that the RMSE value was reduced by 2.1%, 23.7%, and 20.1%, and MAE was decreased by 1.6%, 21.1%, and 22.2%, respectively. Our results showed that the MSSW-LSTM algorithm can achieve higher prediction accuracy and smaller error, and can be applied to GNSS time-series prediction. Full article
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Article
Estimating the Fractional Cycle Biases for GPS Triple-Frequency Precise Point Positioning with Ambiguity Resolution Based on IGS Ultra-Rapid Predicted Orbits
Remote Sens. 2021, 13(16), 3164; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13163164 - 10 Aug 2021
Viewed by 441
Abstract
We investigate the estimation of the fractional cycle biases (FCBs) for GPS triple-frequency uncombined precise point positioning (PPP) with ambiguity resolution (AR) based on the IGS ultra-rapid predicted (IGU) orbits. The impact of the IGU orbit errors on the performance of GPS triple-frequency [...] Read more.
We investigate the estimation of the fractional cycle biases (FCBs) for GPS triple-frequency uncombined precise point positioning (PPP) with ambiguity resolution (AR) based on the IGS ultra-rapid predicted (IGU) orbits. The impact of the IGU orbit errors on the performance of GPS triple-frequency PPP AR is also assessed. The extra-wide-lane (EWL), wide-lane (WL) and narrow-lane (NL) FCBs are generated with the single difference (SD) between satellites model using the global reference stations based on the IGU orbits. For comparison purposes, the EWL, WL and NL FCBs based on the IGS final precise (IGF) orbits are estimated. Each of the EWL, WL and NL FCBs based on IGF and IGU orbits are converted to the uncombined FCBs to implement the static and kinematic triple-frequency PPP AR. Due to the short wavelengths of NL ambiguities, the IGU orbit errors significantly impact the precision and stability of NL FCBs. An average STD of 0.033 cycles is achieved for the NL FCBs based on IGF orbits, while the value of the NL FCBs based on IGU orbits is 0.133 cycles. In contrast, the EWL and WL FCBs generated based on IGU orbits have comparable precision and stability to those generated based on IGF orbits. The use of IGU orbits results in an increased time-to-first-fix (TTFF) and lower fixing rates compared to the use of IGF orbits. Average TTFFs of 23.3 min (static) and 31.1 min (kinematic) and fixing rates of 98.1% (static) and 97.4% (kinematic) are achieved for the triple-frequency PPP AR based on IGF orbits. The average TTFFs increase to 27.0 min (static) and 37.9 min (kinematic) with fixing rates of 97.0% (static) and 96.3% (kinematic) based on the IGU orbits. The convergence times and positioning accuracy of PPP and PPP AR based on IGU orbits are slightly worse than those based on IGF orbits. Additionally, limited by the number of satellites transmitting three frequency signals, the introduction of the third frequency, L5, has a marginal impact on the performance of PPP and PPP AR. The GPS triple-frequency PPP AR performance is expected to improve with the deployment of new-generation satellites capable of transmitting the L5 signal. Full article
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Article
A New Faulty GNSS Measurement Detection and Exclusion Algorithm for Urban Vehicle Positioning
Remote Sens. 2021, 13(11), 2117; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13112117 - 28 May 2021
Cited by 2 | Viewed by 561
Abstract
The performance requirements for Global Navigation Satellite Systems (GNSS) are becoming more demanding as the range of mission-critical vehicular applications, including the Unmanned Aerial Vehicle (UAV) and ground vehicle-based applications, increases. However, the accuracy and reliability of GNSS in some environments, such as [...] Read more.
The performance requirements for Global Navigation Satellite Systems (GNSS) are becoming more demanding as the range of mission-critical vehicular applications, including the Unmanned Aerial Vehicle (UAV) and ground vehicle-based applications, increases. However, the accuracy and reliability of GNSS in some environments, such as in urban areas, are often affected by non-line-of-sight (NLOS) signals and multipath effects. It is therefore essential to develop an effective fault detection scheme that can be applied to GNSS observations so as to ensure that the vehicle positioning can be calculated with a high accuracy. In this paper, we propose an online dataset based faulty GNSS measurement detection and exclusion algorithm for vehicle positioning that takes account of the NLOS/multipath affected scenarios. The proposed algorithm enables a real-time online dataset based fault detection and exclusion scheme, which makes it possible to detect multiple faults in different satellites simultaneously and accurately, thereby allowing real-time quality control of GNSS measurements in dynamic urban positioning applications. The algorithm was tested with simulated/artificial step errors in various scenarios in the measured pseudoranges from a dataset acquired from a UAV in an open area. Furthermore, a real-world test was also conducted with a ground-vehicle driving in a dense urban environment to validate the practical efficiency of the proposed algorithm. The UAV based simulation exhibits a fault detection rate of 100% for both single and multi-satellite fault scenarios, with the horizontal positioning accuracy improved to about 1 metre from tens of metres after fault detection and exclusion. The ground vehicle-based real test shows an overall improvement of 26.1% in 3D positioning accuracy in an urban area compared to the traditional least square method. Full article
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Article
Improving DGNSS Performance through the Use of Network RTK Corrections
Remote Sens. 2021, 13(9), 1621; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13091621 - 21 Apr 2021
Viewed by 550
Abstract
The differential global navigation satellite system (DGNSS) is an enhancement system that is widely used to improve the accuracy of single-frequency receivers. However, distance-dependent errors are not considered in conventional DGNSS, and DGNSS accuracy decreases when baseline length increases. In network real-time kinematic [...] Read more.
The differential global navigation satellite system (DGNSS) is an enhancement system that is widely used to improve the accuracy of single-frequency receivers. However, distance-dependent errors are not considered in conventional DGNSS, and DGNSS accuracy decreases when baseline length increases. In network real-time kinematic (RTK) positioning, distance-dependent errors are accurately modelled to enable ambiguity resolution on the user side, and standard Radio Technical Commission for Maritime Services (RTCM) formats have also been developed to describe the spatial characteristics of distance-dependent errors. However, the network RTK service was mainly developed for carrier-phase measurements on professional user receivers. The purpose of this study was to modify the local-area DGNSS through the use of network RTK corrections. Distance-dependent errors can be reduced, and accuracy for a longer baseline length can be improved. The results in the low-latitude areas showed that the accuracy of the modified DGNSS could be improved by more than 50% for a 17.9 km baseline during solar active years. The method in this paper extends the use of available network RTK corrections with high accuracy to normal local-area DGNSS applications. Full article
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