Theory and Method of GNSS Precision Positioning and Its New Application

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: 15 October 2025 | Viewed by 370

Special Issue Editors


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Guest Editor
School of Automation Science and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
Interests: autonomous navigation; multi-source information fusion; GNSS; human activity recognition; inertial navigation
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Electronic and Information Engineering, Beihang University, Beijing100191, China
Interests: pedestrian inertial positioning; wearable sensor-based positioning; motion recognition
Special Issues, Collections and Topics in MDPI journals
School of Automation Science and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
Interests: intelligent manufacturing; artificial intelligence; deep learning; computer vision
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The aim of this Special Issue is to provide a comprehensive platform for researchers, engineers, and scholars in the field of Global Navigation Satellite System (GNSS) precision positioning to promote in-depth discussions, share the latest research findings, and explore innovative applications related to GNSS precision positioning. By doing so, it hopes to drive the continuous development and improvement of GNSS technology, enhancing its performance and expanding its scope of application in various industries.

This Special Issue welcomes the submission of articles that address various topics related to GNSS precision positioning. It includes both theoretical research regarding improvements in the accuracy, reliability, and integrity of GNSS positioning, as well as practical methods for implementing high-precision positioning in different scenarios. The articles published in this Special Issue will bridge the gap between academic research and real-world applications, aiming to enhance the accessibility and utility of GNSS precision positioning in diverse fields. 

The scope of this Special Issue includes, but is not limited to, the following topics: 

  • Advanced GNSS positioning algorithms, such as new signal processing techniques for better ambiguity resolution and more accurate coordinate estimation.
  • Multi-system and multi-frequency integration in GNSS, exploring how to combine different satellite navigation systems and frequencies to improve positioning performance.
  • GNSS precise positioning in challenging environments, such as urban canyons, forests, and indoor spaces, and the corresponding solutions to overcome signal blockage and interference.
  • The application of GNSS precision positioning in areas such as autonomous driving, surveying and mapping, deformation monitoring, smart city, electricity inspection, and smart agriculture, highlighting the practical value and impact of this technology.

Dr. Qu Wang
Dr. Ming Xia
Dr. Meixia Fu
Guest Editors

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Keywords

  • GNSS precision positioning
  • positioning algorithms
  • multi-system integration
  • environmental impact
  • application fields

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Published Papers (1 paper)

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Research

17 pages, 7673 KiB  
Article
Motion Pattern Recognition via CNN-LSTM-Attention Model Using Array-Based Wi-Fi CSI Sensors in GNSS-Denied Areas
by Ming Xia, Shengmao Que, Nanzhu Liu, Qu Wang and Tuan Li
Electronics 2025, 14(8), 1594; https://doi.org/10.3390/electronics14081594 - 15 Apr 2025
Viewed by 254
Abstract
Human activity recognition (HAR) is vital for applications in fields such as smart homes, health monitoring, and navigation, particularly in GNSS-denied environments where satellite signals are obstructed. Wi-Fi channel state information (CSI) has emerged as a key technology for HAR due to its [...] Read more.
Human activity recognition (HAR) is vital for applications in fields such as smart homes, health monitoring, and navigation, particularly in GNSS-denied environments where satellite signals are obstructed. Wi-Fi channel state information (CSI) has emerged as a key technology for HAR due to its wide coverage, low cost, and non-reliance on wearable devices. However, existing methods face challenges including significant data fluctuations, limited feature extraction capabilities, and difficulties in recognizing complex movements. This study presents a novel solution by integrating a multi-sensor array of Wi-Fi CSI with deep learning techniques to overcome these challenges. We propose a 2 × 2 array of Wi-Fi CSI sensors, which collects synchronized data from all channels within the CSI receivable range, improving data stability and providing reliable positioning in GNSS-denied environments. Using the CNN-LSTM-attention (C-L-A) framework, this method combines short- and long-term motion features, enhancing recognition accuracy. Experimental results show 98.2% accuracy, demonstrating superior recognition performance compared to single Wi-Fi receivers and traditional deep learning models. Our multi-sensor Wi-Fi CSI and deep learning approach significantly improve HAR accuracy, generalization, and adaptability, making it an ideal solution for GNSS-denied environments in applications such as autonomous navigation and smart cities. Full article
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