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Remote Sensing
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Beidou/GNSS Positioning, Navigation and Timing: Methods and Technology (Third Edition)
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Beidou/GNSS Positioning, Navigation and Timing: Methods and Technology (Third Edition)

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 (30 November 2025) | Viewed by 1080

Special Issue Editors

Prof. Dr. Baocheng Zhang

E-Mail Website
Guest Editor
Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan 430077, China
Interests: GNSS; precise point positioning; PPP-RTK
Special Issues, Collections and Topics in MDPI journals
Dr. Robert Odolinski

E-Mail Website
Guest Editor
National School of Surveying, University of Otago, 310 Castle Street, Dunedin 9016, New Zealand
Interests: multi-GNSS precise positioning; integer ambiguity resolution; low-cost GNSS receiver
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Multi-frequency and multi-constellation GNSS, an effective tool for providing precise navigation and positioning, plays a significant role in various fields such as geological monitoring, urban services, and global meteorology. In addition, the Beidou Satellite Navigation System (BDS) is a global navigation satellite system developed by China, the third generation of which achieved global coverage of timing and navigation in 2020. All of these services rely on fundamental theories, models, and algorithms to pinpoint the position and speed of each spacecraft. Beidou/GNSS will inevitably involve more applications in the future; therefore, the reliability and timeliness of data processing, including estimations, quality control, and other aspects, still need to be improved and perfected.

We are pleased to announce the launch of a new Special Issue in Remote Sensing with the aim of collecting papers on BDS/GNSS positioning algorithms, integrated navigation, and data processing for Earth science applications. Research topics include but are not limited to the following: (a} satellite orbit dynamics (solar radiation pressure, attitude); (b) ground-based and space-borne GNSS receivers monitoring the global ionospheric climate, weather, and low-orbit GNSS to retrieve environmental parameters on land and at sea; and (c) Earth observations that integrate GNSS with geodesy and geophysics, such as the Global Geodesy Observation System—GGOS.

Prof. Dr. Baocheng Zhang
Dr. Robert Odolinski
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 250 words) can be sent to the Editorial Office for assessment.

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 and multi-constellation GNSS
  • BDS
  • POD/LEO
  • navigation and timing
  • geodesy and geophysics
  • the advance of high-precision products

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Related Special Issue

Published Papers (2 papers)

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Research

19 pages, 11006 KB  
Article
Research on GPS Satellite Clock Bias Prediction Algorithm Based on the Inaction Method
by Cong Shen, Huiwen Hu, Guocheng Wang, Lintao Liu, Dong Ren and Zhiwu Cai
Remote Sens. 2025, 17(24), 4013; https://doi.org/10.3390/rs17244013 - 12 Dec 2025
Viewed by 149
Abstract
Satellite clock bias exhibits complex, time-varying periodic characteristics due to environmental disturbances. Accurate modeling and prediction of periodic terms play a crucial role in improving the precision and stability of short-term predictions. Traditional models such as spectral analysis model (SAM) estimate the frequency, [...] Read more.
Satellite clock bias exhibits complex, time-varying periodic characteristics due to environmental disturbances. Accurate modeling and prediction of periodic terms play a crucial role in improving the precision and stability of short-term predictions. Traditional models such as spectral analysis model (SAM) estimate the frequency, amplitude, and phase of periodic terms through global fitting, which limits their ability to adapt to abrupt changes at the prediction boundary. To address this limitation, this paper proposes an improved spectral analysis model (IM-SAM) based on the inaction method (IM). The model employs IM to extract the instantaneous frequency, amplitude, and phase parameters of periodic terms precisely at the data endpoint, and utilizes the parameters of periodic terms at the data endpoint for prediction, effectively suppressing periodic fluctuations in prediction errors. Experimental results based on real GPS clock bias data demonstrate that the root mean square (RMS) of IM-SAM prediction errors is reduced by 19.14%, 14.39%, and 10.48% for 3 h, 6 h, and 12 h prediction tasks, respectively, compared with SAM. Furthermore, a kinematic precise point positioning experiment was performed using IM-SAM-predicted clock products and compared with the predicted half of IGS ultra-rapid clock products. The RMS of position error was reduced by 14.3%, 12.6%, and 7.9% in the east, north, and up directions, respectively. These results demonstrate the practical effectiveness and accuracy of IM-SAM in real-time clock prediction and GPS positioning applications. Full article
(This article belongs to the Special Issue Beidou/GNSS Positioning, Navigation and Timing: Methods and Technology (Third Edition))
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26 pages, 5976 KB  
Article
A Hybrid-Weight TOPSIS and Clustering Approach for Optimal GNSS Station Selection in Multi-GNSS Precise Orbit Determination
by Weitong Jin, Xing Li, Liang Chen, Chuanzhen Sheng, Yongqiang Yuan, Keke Zhang, Xingxing Li, Jingkui Zhang, Xulun Zhang and Baoguo Yu
Remote Sens. 2025, 17(21), 3548; https://doi.org/10.3390/rs17213548 - 26 Oct 2025
Viewed by 542
Abstract
The accuracy of Precise Orbit Determination (POD) for Global Navigation Satellite Systems (GNSS) critically depends on optimal tracking station selection. This study proposed and validates a novel framework that integrates a hybrid-weight Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) [...] Read more.
The accuracy of Precise Orbit Determination (POD) for Global Navigation Satellite Systems (GNSS) critically depends on optimal tracking station selection. This study proposed and validates a novel framework that integrates a hybrid-weight Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) model with spherical k-means clustering, effectively resolving the challenge of balancing station data quality with uniform spatial distribution. The framework generates by first a comprehensive quality score for each station based on 40 indicators and then selects the top-scoring station from distinct geographical clusters to construct a well-distributed, high-quality network. To validate the methodology, we performed multi-GNSS POD using networks of 30, 60, and 90 stations selected by the proposed framework. The accuracy was assessed via two independent methods: orbit comparisons (Root Mean Square, RMS) against final Analysis Center (AC) orbits and Satellite Laser Ranging (SLR) validation. The results demonstrate that the optimized 60-station network (e.g., RMS of ~2.5, 5.3, 2.1, and 5.4 cm for GPS, GLONASS, Galileo, and BDS, respectively) achieves an accuracy comparable to that of a 90-station network. Moreover, a 30-station globally uniform network outperforms a 90-station network of high-quality but spatially clustered stations. This study provides an objective and quantitative solution for establishing efficient and reliable GNSS tracking networks, directly benefiting ACs and other high-precision applications. Full article
(This article belongs to the Special Issue Beidou/GNSS Positioning, Navigation and Timing: Methods and Technology (Third Edition))
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