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Remote Sensing
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Advances in Multi-GNSS Technology and Applications
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Advances in Multi-GNSS Technology and Applications

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

Deadline for manuscript submissions: 15 September 2024 | Viewed by 427

Special Issue Editors

Dr. Bobin Cui

E-Mail Website
Guest Editor
1. College of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, China
2. Deutsches GeoForschungsZentrum (GFZ), Potsdam, Germany
Interests: multi-GNSS
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

Special Issue Information

Dear Colleagues,

The global navigation satellite system (GNSS) arena comprises four primary global systems—GPS, GLONASS, Galileo, and BDS—as well as two regional systems, QZSS and IRNSS. The fusion of these multi-GNSS systems into various devices and services unlocks new opportunities and challenges, necessitating the adoption of advanced methodologies from high-precision and geoscience fields. This integration enhances signal geometry, ensures redundancy, and extends coverage, especially in difficult environments. Algorithmic progress is crucial for leveraging these opportunities and tackling the challenges to improve the precision, availability, interoperability, and integrity of practical GNSS applications. Multi-GNSS is vital for its role in facilitating cutting-edge applications that demand high-precision navigation, such as autonomous vehicles and disaster management, and for maintaining reliable services essential to safety-critical operations. Moreover, it promotes international cooperation, aids in establishing global standards, and propels the evolution of satellite navigation technology, leading to a more interconnected and accurate world.

A Special Issue of the open access journal Remote Sensing (ISSN 2072-4292) is now underway, focusing on ‘Advances in Multi-GNSS Technology and Applications’; it delves into the expanding realm of global navigation satellite systems (GNSSs), presenting both opportunities and challenges in delivering reliable position, navigation, and timing solutions crucial for contemporary human endeavors. We invite submissions covering GNSS receivers, positioning algorithms, contemporary applications, and software tool developments for data collection and processing, along with their applications in diverse fields. This Special Issue seeks to foster dialogue and collaboration in advancing the understanding and utilization of multi-GNSS technology across disciplines.

Contributions may include original research articles, reviews, case studies, and technical notes that provide insights into the current state of the art and future directions in the field of multi-GNSS technology and its diverse applications.

Articles may address, but are not limited, to the following topics:

  • Multi-GNSS techniques, algorithms, and methodologies;
  • High-precision GNSS methods;
  • New methods for atmospheric modeling and applications;
  • Advances in GNSS signal processing and theoretical modeling;
  • Multi-sensor applications;
  • Next-generation signal design for navigation purposes;
  • GNSS signal processing, positioning, navigation, and timing;
  • GNSS integrity monitoring, interference mitigation, and novel applications.

Dr. Bobin Cui
Dr. Jungang Wang
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

  • multi-GNSS
  • multi-sensors
  • positioning navigation and timing service
  • GNSS integrity monitoring
  • GNSS signal processing
  • multi-technique integration

Published Papers (1 paper)

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Research

20 pages, 6437 KiB  
Article
Prediction of Deformation in Expansive Soil Landslides Utilizing AMPSO-SVR
by Zi Chen, Guanwen Huang and Yongzhi Zhang
Remote Sens. 2024, 16(13), 2483; https://doi.org/10.3390/rs16132483 - 6 Jul 2024
Viewed by 219
Abstract
A non-periodic “step-like” variation in displacement is exhibited owing to the repeated instability of expansive soil landslides. The dynamic prediction of deformation for expansive soil landslides has become a challenge in actual engineering for disaster prevention and mitigation. Therefore, a support vector regression [...] Read more.
A non-periodic “step-like” variation in displacement is exhibited owing to the repeated instability of expansive soil landslides. The dynamic prediction of deformation for expansive soil landslides has become a challenge in actual engineering for disaster prevention and mitigation. Therefore, a support vector regression prediction (AMPSO-SVR) model based on adaptive mutation particle swarm optimization is proposed, which is suitable for small samples of data. The shallow displacement is decomposed into a trend component and fluctuating component by complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), and the trend displacement is predicted by cubic polynomial fitting. In this paper, the multiple disaster-inducing factors of expansive landslides and the time hysteresis effect between displacement and its influencing factors are fully considered, and the crucial influencing factors which eliminate the time lag effect and state factors are input into the model to predict the fluctuation displacement. Monitoring data in the Ningming area of China are employed for the model validation. The predicted results are compared with those of the traditional model. The model performance is evaluated through indicators such as the goodness of fit R2 and root mean square error RMSE. The results show that the prediction RMSE of the new model for three monitoring stations can reach 2.6 mm, 6.6 mm, and 2.5 mm, respectively. Compared with the common Grid search support vector regression (GS-SVR), the Particle Swarm Optimization Support Vector Regression (PSO-SVR) and Back Propagation Neural Network (BPNN) models have average improvements of 58.4%, 38.1%, and 25.2% respectively. The goodness of fit R2 is superior to 0.99 in the new method. The proposed model can effectively be deployed for the displacement prediction of non-periodic stepped expansive soil landslides driven by multiple influencing factors, providing a reference idea for the deformation prediction of expansive soil landslides. Full article
(This article belongs to the Special Issue Advances in Multi-GNSS Technology and Applications)
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