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GNSS Position, Navigation, and Remote Sensing Based on Multiple Source Observation Fusing

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Satellite Missions for Earth and Planetary Exploration".

Deadline for manuscript submissions: closed (31 March 2025) | Viewed by 3981

Special Issue Editors

Dr. Jungang Wang

E-Mail Website
Guest Editor
GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
Interests: space geodetic techniques; global navigation satellite systems; atmospheric delay modeling; precise orbit determination
Special Issues, Collections and Topics in MDPI journals
Dr. Haibo Ge

E-Mail Website
Guest Editor
College of Surveying and Geo-Informatics, Tongji University, Shanghai, China
Interests: GNSS precise orbit and clock determination; LEO enhanced GNSS; next-generation GNSS
Special Issues, Collections and Topics in MDPI journals
Dr. Kai Zheng

E-Mail Website
Guest Editor
School of Navigation, Wuhan University of Technology, Wuhan 430063, China
Interests: GNSS precision positioning; speed and attitude measurement; GNSS geoscience application; integrated navigation
Dr. Kyriakos Balidakis

E-Mail Website
Guest Editor
GFZ German Research Centre for Geosciences, Department of Geodesy, 14473 Potsdam, Germany
Interests: geodesy; very long baseline interferometry; atmospheric refraction; ray-tracing; geophysical loading; integrated water vapor; numerical weather prediction; combination of space geodetic techniques
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Serge Reboul

E-Mail Website
Guest Editor
Laboratoire d’Informatique Signal et Image de la Côte d’Opale (LISIC), Université du Littoral Côte d’Opale (ULCO), Maison de la Recherche Blaise Pascal BP 719, 62228 Calais CEDEX, France
Interests: signal processing; information fusion; GNSS; radar; GNSS-reflectometry
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Maorong Ge

E-Mail Website
Guest Editor
German Research Centre for Geosciences (GFZ), Telegrafenberg, 14473 Potsdam, Germany
Interests: GNSS positioning and navigation; precise orbit determination; multi-sensor fusion; GNSS remote sensing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid development of Global Navigation Satellite Systems (GNSS) has brought forth new opportunities and challenges in providing precise positioning, navigation, and timing (PNT) services essential for various applications for Earth observing, geohazard monitoring and early warning, and civil applications. This Special Issue aims to (1) explore the intersection of GNSS with multi-source observations, encompassing diverse satellite systems (GPS, GLONASS, Galileo, BDS, etc.), Low Earth Orbiter (LEO) platforms, and other instruments such as inertial system, Lidar, visual sensors, to improve the accuracy, reliability, and robust of GNSS-based PNT services; and (2) discover the fusion of GNSS with other space-based Earth observing technologies such as satellite altimetry, GNSS Reflectometry, and InSAR, coupled with ground-based technologies such as radiosonde and ionosonde, to provide enhanced terrestrial and space weather monitoring data characterized by improved spatial and temporal resolutions.

Contributions to this Special Issue are invited to cover recent advances, challenges, and applications in GNSS technology, positioning algorithms, and remote sensing methodologies. We welcome both theoretical and applied research that explores the synergies between GNSS and other observational sources, fostering innovation in geoscience applications and high-precision positioning. Topics of interest include:

  • Advanced GNSS positioning algorithms and methodologies.
  • Integration of GNSS with other satellite-based observations for improved accuracy.
  • Integrated processing of multi-GNSS and LEO observations.
  • Applications of GNSS in remote sensing.
  • Utilization of multi-source observations for enhanced terrestrial weather and space weather monitoring.
  • Next-generation navigation technologies leveraging multi-source observations.
  • Earthquake, tsunami, and volcano monitoring and early warning using real-time GNSS.
  • GNSS Reflectometry.
  • GNSS Signal Processing.

This Special Issue provides a platform for researchers to share their latest findings, methodologies, and insights, contributing to the collective knowledge in the field. We encourage submissions that bridge the gap between GNSS positioning, navigation, and remote sensing, showcasing the potential of multi-source observations to address contemporary challenges.

We look forward to your valuable contributions to this vibrant and interdisciplinary exploration of GNSS.

Dr. Jungang Wang
Dr. Haibo Ge
Prof. Dr. Kai Zheng
Dr. Kyriakos Balidakis
Prof. Dr. Serge Reboul
Prof. Dr. Maorong Ge
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 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

  • global navigation satellite systems
  • low earth orbiter
  • positioning, navigation, and timing
  • GNSS remote sensing
  • multi-sensor fusion
  • precise GNSS orbit and clock determination
  • geohazard monitoring and early warning GNSS reflectometry GNSS signal processing

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

22 pages, 10504 KiB  
Article
Experimental Validation of a GNSS Receiver Antenna Absolute Field Calibration System
by Antonio Tupek, Mladen Zrinjski, Krunoslav Špoljar and Karlo Stipetić
Remote Sens. 2025, 17(1), 64; https://doi.org/10.3390/rs17010064 - 27 Dec 2024
Viewed by 653
Abstract
Carrier-phase measurements are essential in precise Global Navigation Satellite System (GNSS) positioning applications. The quality of those observations, as well as the final positioning result, is influenced by an extensive list of GNSS error sources, one of which is the receiver antenna phase [...] Read more.
Carrier-phase measurements are essential in precise Global Navigation Satellite System (GNSS) positioning applications. The quality of those observations, as well as the final positioning result, is influenced by an extensive list of GNSS error sources, one of which is the receiver antenna phase center (PC) model. It has been well established that the antenna PC exhibits variability depending on the frequency, direction, and intensity of the incoming GNSS signal. To mitigate the corresponding range errors, phase center corrections (PCCs) are determined through a specialized procedure known as receiver antenna calibration and subsequently applied in data processing. In 2023, the Laboratory for Measurements and Measuring Technique (LMMT) of the Faculty of Geodesy, University of Zagreb, Croatia, initiated the development of a new robotic GNSS receiver antenna calibration system. The system implements absolute field calibration and PCC modeling through triple-difference (TD) carrier-phase observations and spherical harmonics (SH) expansion. This study presents and documents dual-frequency (L1 and L2) Global Positioning System (GPS) calibration results for several distinct receiver antennas. Furthermore, the main goals of this contribution are to evaluate the accuracy of dual-frequency GPS calibration results on the pattern level with respect to independent calibrations obtained from Geo++ GmbH and to extensively experimentally validate LMMT calibration results in the spatial (coordinate) domain, i.e., to investigate how the application of LMMT PPC models reflects on geodetic-grade GNSS positioning. Our experimental research results showed a submillimeter calibration accuracy, i.e., 0.36 mm for GPS L1 and 0.54 mm for the GPS L2 frequency. Furthermore, our field results confirmed that the application of LMMT PCC models significantly increases baseline accuracy and GNSS network solution accuracy when compared to type-mean PCC models of the International GNSS Service (IGS). Full article
(This article belongs to the Special Issue GNSS Position, Navigation, and Remote Sensing Based on Multiple Source Observation Fusing)
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17 pages, 4968 KiB  
Article
A Refined Spatiotemporal ZTD Model of the Chinese Region Based on ERA and GNSS Data
by Yongzhao Fan, Fengyu Xia, Zhimin Sha and Nana Jiang
Remote Sens. 2024, 16(23), 4515; https://doi.org/10.3390/rs16234515 - 2 Dec 2024
Viewed by 758
Abstract
Empirical tropospheric models can improve the performance of GNSS precise point positioning (PPP) by providing a priori zenith tropospheric delay (ZTD) information. However, existing models experience insufficient ZTD profile refinement, inadequate correction for systematic bias between the ZTD used in empirical modelling and [...] Read more.
Empirical tropospheric models can improve the performance of GNSS precise point positioning (PPP) by providing a priori zenith tropospheric delay (ZTD) information. However, existing models experience insufficient ZTD profile refinement, inadequate correction for systematic bias between the ZTD used in empirical modelling and the GNSS ZTD, and low time efficiency in model updating as more data become available. Therefore, a refined spatiotemporal empirical ZTD model was developed in this study on the basis of the fifth generation of European Centre for Medium-Range Weather Forecasts Reanalysis (ERA5) data and GNSS data. First, an ENM-R profile model was established by refining the modelling height of the negative exponential function model (ENM). Second, a regression kriging interpolation method was designed to model the systematic bias correction between the ERA5 ZTD and the GNSS ZTD. Last, the final refined ZTD model, ENM-RS, was established by introducing systematic bias correction into ENM-R. Experiments suggest that, compared with the ENM-R and GPT3 models, ENM-RS can effectively suppress systematic bias and improve ZTD modelling accuracy by 10~17%. To improve model update efficiency, the idea of updating an empirical model with sequential least square (SLSQ) adjustment is proposed for the first time. When ENM-RS is modelled via 12 years of ERA data, our method can reduce the time consumption to one-fifth of that of the traditional method. The benefits of our ENM-RS model are evaluated with PPP. The results show that relative to PPP solutions with ENM-R- and GPT3-derived ZTD constraints as well as no constraint, the ENM-RS ZTD constraint can decrease PPP convergence time by approximately 10~30%. Full article
(This article belongs to the Special Issue GNSS Position, Navigation, and Remote Sensing Based on Multiple Source Observation Fusing)
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23 pages, 7491 KiB  
Article
LEO-Enhanced GNSS/INS Tightly Coupled Integration Based on Factor Graph Optimization in the Urban Environment
by Shixuan Zhang, Rui Tu, Zhouzheng Gao, Decai Zou, Siyao Wang and Xiaochun Lu
Remote Sens. 2024, 16(10), 1782; https://doi.org/10.3390/rs16101782 - 17 May 2024
Cited by 2 | Viewed by 1785
Abstract
Precision point positioning (PPP) utilizing the Global Navigation Satellite System (GNSS) is a traditional and widely employed technology. Its performance is susceptible to observation discontinuities and unfavorable geometric configurations. Consequently, the integration of the Inertial Navigation System (INS) and GNSS makes full use [...] Read more.
Precision point positioning (PPP) utilizing the Global Navigation Satellite System (GNSS) is a traditional and widely employed technology. Its performance is susceptible to observation discontinuities and unfavorable geometric configurations. Consequently, the integration of the Inertial Navigation System (INS) and GNSS makes full use of their respective advantages and effectively mitigates the limitations of GNSS positioning. However, the GNSS/INS integration faces significant challenges in complex and harsh urban environments. In recent years, the geometry between the user and the satellite has been effectively improved with the advent of lower-orbits and faster-speed Low Earth Orbit (LEO) satellites. This enhancement provides more observation data, opening up new possibilities and opportunities for high-precision positioning. Meanwhile, in contrast to the traditional extended Kalman filter (EKF) approach, the performance of the LEO-enhanced GNSS/INS tightly coupled integration (TCI) can be significantly improved by employing the factor graph optimization (FGO) method with multiple iterations to achieve stable estimation. In this study, LEO data and the FGO method were employed to enhance the GNSS/INS TCI. To validate the effectiveness of the method, vehicle data and simulated LEO observations were subjected to thorough analysis. The results suggest that the integration of LEO data significantly enhances the positioning accuracy and convergence speed of the GNSS/INS TCI. In contrast to the FGO GNSS/INS TCI without LEO enhancement, the average enhancement effect of the LEO is 22.16%, 7.58%, and 10.13% in the north, east, and vertical directions, respectively. Furthermore, the average root mean square error (RMSE) of the LEO-enhanced FGO GNSS/INS TCI is 0.63 m, 1.21 m, and 0.85 m in the north, east, and vertical directions, respectively, representing an average improvement of 41.91%, 13.66%, and 2.52% over the traditional EKF method. Meanwhile, the simulation results demonstrate that LEO data and the FGO method effectively enhance the positioning and convergence performance of GNSS/INS TCI in GNSS-challenged environments (tall buildings, viaducts, underground tunnels, and wooded areas). Full article
(This article belongs to the Special Issue GNSS Position, Navigation, and Remote Sensing Based on Multiple Source Observation Fusing)
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