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Remote Sensing
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Advances in Multi-Frequency GNSS High-Precision Positioning and Navigation Technology
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Advances in Multi-Frequency GNSS High-Precision Positioning and Navigation Technology

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: 31 March 2026 | Viewed by 2335

Special Issue Editors

Dr. Wang Gao

E-Mail Website
Guest Editor
School of Instrument Science and Engineering, Southeast University, Nanjing, China
Interests: GNSS high-precision positioning; multi-sensors integrated navigation and positioning
Special Issues, Collections and Topics in MDPI journals
Dr. Rui Shang

E-Mail Website
Guest Editor Assistant
School of Transportation, Southeast University, 2 Southeast University Road, Nanjing 211189, China
Interests: multi-GNSS RTK; PPP; PPP-B2b; smartphone
Dr. Qing Zhao

E-Mail Website
Guest Editor Assistant
School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
Interests: BDS; GNSS; PPP-RTK; LEO; multi-frequency; atmospheric modelling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Global Navigation Satellite Systems (GNSSs) have revolutionized positioning, navigation, and timing (PNT) technologies, serving as a cornerstone for applications ranging from autonomous vehicles and precision agriculture to disaster monitoring and geodetic surveying. The advent of multi-frequency signals from modernized GNSS constellations (e.g., GPS L5, Galileo E5/E6, BDS-3 B1c/B2a/B2b, and GLONASS L3) has unlocked unprecedented opportunities for enhancing the accuracy, reliability, and convergence speed of high-precision positioning. Multi-frequency GNSSs enable advanced signal processing techniques, such as improved ambiguity resolution, better mitigation of ionospheric delays, and enhanced robustness against environmental disturbances. However, challenges persist in fully exploiting these signals, including in the development of efficient multi-frequency RTK/PPP/PPP-RTK models, handling inter-frequency biases, ensuring system integrity, and deriving high-resolution atmospheric products. This Special Issue aims to address these challenges by showcasing cutting-edge research and fostering interdisciplinary collaboration in multi-frequency GNSS technology.

This Special Issue seeks to compile high-quality research and review articles that advance the theory, algorithms, and applications of multi-frequency GNSS in high-precision positioning and navigation. By focusing on innovations in signal processing, error modeling, and system integration, this collection will highlight how multi-frequency GNSS can address emerging demands in both scientific and industrial domains.

Remote sensing emphasizes the use of satellite-based and remote sensing technologies for Earth observation and spatial data analysis. The Special Issue aligns with the journal’s scope by exploring GNSSs as a critical remote sensing tool for atmospheric studies, deformation monitoring, and real-time navigation—all of which rely on advancements in multi-frequency signal utilization.

We invite submissions addressing, but not limited to, the following themes:

  • Multi-frequency GNSS Positioning Models:

RTK, PPP, PPP-RTK algorithms leveraging multi-frequency signals;

Inter-system and inter-frequency bias estimation/calibration.

  • Ambiguity Resolution and Error Mitigation:

New methods for fast and reliable multi-frequency ambiguity resolution;

Ionospheric/tropospheric delay modeling and real-time correction;

Multi-sensor integration (e.g., INS, LiDAR) for robust navigation.

  • GNSS Integrity and Atmospheric Applications:

Integrity monitoring frameworks for safety-critical systems;

GNSS-derived atmospheric products (e.g., ionospheric TEC, tropospheric zenith delays);

Crowdsourced GNSS data for weather forecasting and climate studies.

  • Emerging Technologies and Datasets:

Low Earth Orbit (LEO) satellite-augmented GNSS positioning;

Machine learning/AI-driven approaches for multi-frequency signal processing.

Article Types: Original research articles, comprehensive reviews, case studies, and technical notes are welcome. Submissions should demonstrate methodological rigor, novelty, and practical relevance.

Dr. Wang Gao
Guest Editor

Dr. Rui Shang
Dr. Qing Zhao
Guest Editor Assistants

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

  • multi-frequency GNSS
  • high-precision positioning
  • ambiguity resolution
  • RTK/PPP/PPP-RTK
  • GNSS integrity
  • inter-frequency bias estimation/calibration
  • multi-frequency GNSS bias product estimation

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  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
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  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

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

Published Papers (3 papers)

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Research

25 pages, 11376 KB  
Article
Best Integer Equivariant (BIE) Ambiguity Resolution Based on Tikhonov Regularization for Improving the Positioning Performance in Weak GNSS Models
by Wang Gao, Kexin Liu, Xianlu Tao, Sai Wu, Wenxin Jin and Shuguo Pan
Remote Sens. 2025, 17(17), 3053; https://doi.org/10.3390/rs17173053 - 2 Sep 2025
Viewed by 847
Abstract
In complicated scenarios, due to the low precision of float solutions and poor reliability of fixed solutions, it is challenging to achieve a balance between accuracy and reliability of the integer least squares (ILS) estimation. To address this dilemma, the best integer equivariant [...] Read more.
In complicated scenarios, due to the low precision of float solutions and poor reliability of fixed solutions, it is challenging to achieve a balance between accuracy and reliability of the integer least squares (ILS) estimation. To address this dilemma, the best integer equivariant (BIE) estimation, which makes a weighted sum of all possible candidates, has recently been attached great importance. The BIE solution approaches the float solution at a low ILS success rate, maintaining positioning reliability. As the success rate increases, it converges to the fixed solution, facilitating high-precision positioning. Furthermore, the posterior variance of BIE estimation provides the capability of reliability evaluation. However, in environments with a limited number or a deficient configuration of available satellites, there is a sharp decline in the strength of the GNSS precise positioning model. In this case, the exactness of weight allocation for integer candidates in BIE estimation will be severely compromised by unmodeled errors. When the ambiguity is incorrectly fixed, the wrongly determined optimal candidate is probably assigned an excessively high weight. Therefore, the BIE solution in a weak GNSS model always exhibits a significant positioning error consistent with the fixed solution. Moreover, the posterior variance of BIE estimation approximately resembles that of a fixed solution, losing error warning ability. Consequently, the BIE estimation may exhibit lower reliability compared to the ILS estimation employing a validation test with a loose acceptance threshold. To improve the positioning performance in weak GNSS models, a BIE ambiguity resolution (AR) method based on Tikhonov regularization is proposed in this paper. The method introduces Tikhonov regularization into the least squares (LS) estimation and the ILS ambiguity search, mitigating the serious impact of unmodeled errors on the BIE estimation under weak observation conditions. Meanwhile, the regularization factors are appropriately selected by utilizing an optimized approach established on the L-curve method. Simulation experiments and field tests have demonstrated that the method can significantly enhance the positioning accuracy and reliability in weak GNSS models. Compared to the traditional BIE estimation, the proposed method achieved accuracy improvements of 73.6% and 69.3% in the field tests with 10 km and 18 km baselines, respectively. Full article
(This article belongs to the Special Issue Advances in Multi-Frequency GNSS High-Precision Positioning and Navigation Technology)
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19 pages, 3553 KB  
Article
Research on the Autonomous Orbit Determination of Beidou-3 Assisted by Satellite Laser Ranging Technology
by Wei Xiao, Zhengcheng Wu, Zongnan Li, Lei Fan, Shiwei Guo and Yilun Chen
Remote Sens. 2025, 17(14), 2342; https://doi.org/10.3390/rs17142342 - 8 Jul 2025
Viewed by 642
Abstract
The Beidou Global System (BDS-3) innovatively achieves autonomous navigation using inter-satellite links (ISL) across the entire constellation, but it still faces challenges such as the limitations of the prior constraint orbital accuracy and the overall constellation rotation. The gradual availability of satellite laser [...] Read more.
The Beidou Global System (BDS-3) innovatively achieves autonomous navigation using inter-satellite links (ISL) across the entire constellation, but it still faces challenges such as the limitations of the prior constraint orbital accuracy and the overall constellation rotation. The gradual availability of satellite laser ranging (SLR) data, with advantages of high precision and no ambiguous parameters, can provide new ideas for solving the current problem. This work firstly deduces the mathematical model for orbit determination by combining inter-satellite links and the introduced satellite laser ranging observations, then designs orbit determination experiments with different prior orbit constraints and different observation data, and finally evaluates the impacts of the prior orbits and the introduction of SLR observations from two dimensions: orbit accuracy and constellation rotation. The experimental results using one month of measured data show the following: (1) There is good consistency among different days, and the accuracy of the prior orbits affects the performance of the orbit determination and the consistency. Compared with broadcast ephemerides, using precise ephemerides as prior constraints significantly improves the consistency, and the orbit accuracy can be increased by about 75%. (2) The type of observation data affects the performance of the orbit determination. Introducing SLR observations can improve the orbit accuracy by approximately 13% to 26%. (3) Regardless of whether broadcast ephemerides or precise ephemerides are used as prior constraints, the constellation translation and rotation still exist after introducing SLR observations. Among the translation parameters, TX is the largest, followed by TY, and TZ is the smallest; all three rotation parameters (RX, RY, and RZ) show relatively large values, which may be related to the limited number of available satellite laser ranging stations during this period. (4) After considering the constellation translation and rotation, the orbit accuracy under different prior constraints remains at the same level. The statistical root mean square error (RMSE) indicates that the orbit accuracy of inclined geosynchronous orbit (IGSO) satellites in three directions is better than 20 cm, while the accuracy of medium earth orbit (MEO) satellites in along-track, cross-track, and radial directions is better than 10 cm, 8 cm, and 5 cm, respectively. Full article
(This article belongs to the Special Issue Advances in Multi-Frequency GNSS High-Precision Positioning and Navigation Technology)
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31 pages, 2735 KB  
Article
An Optimization Method for Indoor Pseudolites Anchor Layout Based on MG-MOPSO
by Xiaohu Liang, Shuguo Pan, Shitong Du, Baoguo Yu and Shuang Li
Remote Sens. 2025, 17(11), 1909; https://doi.org/10.3390/rs17111909 - 30 May 2025
Viewed by 514
Abstract
To address the challenge of optimizing the layout of pseudolite anchor points in complex indoor environments with significant occlusions, this paper proposes a multi-objective particle swarm optimization algorithm (MG-MOPSO). The algorithm leverages a minimum geometric dilution of precision (GDOP) configuration to optimize anchor [...] Read more.
To address the challenge of optimizing the layout of pseudolite anchor points in complex indoor environments with significant occlusions, this paper proposes a multi-objective particle swarm optimization algorithm (MG-MOPSO). The algorithm leverages a minimum geometric dilution of precision (GDOP) configuration to optimize anchor deployment, aiming to meet the high-precision requirements of indoor pseudolite positioning systems. Experimental results show that compared to the standard MOPSO, MG-MOPSO improves the convergence speed of two objective functions by 21.43% and 25.81%, respectively, and enhances optimization accuracy by 29.41% and 10%. Compared to the non-dominated sorting genetic algorithm II (NSGA-II), the convergence speed increases by 33.33% and 36.99%, while optimization accuracy improves by 36.84% and 29.41%. Moreover, MG-MOPSO outperforms both standard MOPSO and NSGA-II in terms of the Pareto front’s convergence and diversity, with improvements of 16.8% and 14.7%, respectively. Additionally, significant reductions are observed in average positioning error, maximum positioning error, and standard deviation across multiple test points. These results validate the effectiveness of the minimum-GDOP-based initialization and segmented weighting strategy, demonstrating the superior performance and broad applicability of the proposed MG-MOPSO algorithm in optimizing pseudolite layouts under complex indoor occlusion conditions. Full article
(This article belongs to the Special Issue Advances in Multi-Frequency GNSS High-Precision Positioning and Navigation Technology)
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