New Advances in Navigation and Positioning Systems

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 15 October 2024 | Viewed by 727

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
Key Laboratory of Industrial Internet of Things & Networked Control, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
Interests: indoor localization; wireless sensing
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

E-Mail Website
Guest Editor
School of Electronic and Information Engineering, Beihang University, Beijing 100191, China
Interests: pedestrian inertial positioning; wearable sensor-based positioning; motion recognition

Special Issue Information

Dear Colleagues,

Navigation and location services are basic needs of human social life. They play a basic supporting role in various military and civilian fields and are widely used in emergency rescue, public safety, mass travel, Internet of Things, smart cities, and other fields. To provide seamless and high-precision indoor and outdoor location-based services, researchers have paid increasing attention to indoor positioning. Various indoor positioning and tracking technologies have been applied in academia as well as in industry, ranging from RFID, Zigbee, UWB, Wi-Fi, Bluetooth, visible light, IMU, to magnetic field. However, currently, a general technique widely used, like GNSS, is absent. Each method has its inherent strengths and weaknesses. No single technology dominates the others in terms of accuracy, power consumption, and portability in all practical scenarios.

The aim of the present Special Issue is to foster advances in user activity and location awareness for a wide range of practical applications and research studies. We encourage the submission of both theoretical and applied research results focused on various aspects, including but not limited to, the following:

  • Human activity recognition;
  • Floor recognition;
  • Indoor/outdoor recognition;
  • Autonomous positioning and navigation;
  • Pedestrian positioning;
  • Robot navigation;
  • Magnetic positioning;
  • Radio frequency positioning;
  • Multi-source positioning;
  • Digital twin;
  • Intelligent vehicle;
  • GNSS and applications;
  • Location privacy-preserving.

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

Manuscript Submission Information

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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. Electronics 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 2400 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

  • location-based services
  • multi-source fusion
  • pedestrian dead reckoning
  • simultaneous localization and mapping
  • indoor navigation
  • indoor localization
  • pedestrian navigation
  • human activity recognition
  • vehicle positioning
  • Internet of Things
  • artificial intelligence
  • deep learning

Published Papers (1 paper)

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Research

20 pages, 4622 KiB  
Article
Fingerprint-Based Localization Enabled by Low-Rank Matrix Reconstruction in Intelligent Reflective Surface-Assisted Networks
by Shiru Duan, Yuexia Zhang and Ruiqi Liu
Electronics 2024, 13(9), 1743; https://doi.org/10.3390/electronics13091743 - 1 May 2024
Viewed by 350
Abstract
The intelligent reflective surface (IRS) is a novel network node that consists of a large-scale passive reflective array to obtain a customized reflected wave direction by modulating the amplitude phase, which can be easily deployed to change the wireless signal propagation environment and [...] Read more.
The intelligent reflective surface (IRS) is a novel network node that consists of a large-scale passive reflective array to obtain a customized reflected wave direction by modulating the amplitude phase, which can be easily deployed to change the wireless signal propagation environment and enhance the communication performance under a non-line-of-sight (NLOS) environment, where location services cannot perform accurately. In this study, a low-rank matrix reconstruction-enabled fingerprint-based localization algorithm for IRS-assisted networks is proposed. Firstly, a 5G positioning system based on IRSs is constructed using multiple IRSs deployed to reflect signals. This enables the base station to overcome the influence of NLOS and receive the positioning signal of the point to be positioned. Then, the angular domain power expectation matrix of the received signal is extracted as a fingerprint to form a partial fingerprint database. Next, the complete fingerprint database is reconstructed using the low-rank matrix fitting algorithm, thereby considerably reducing the workload of building the fingerprint database. Finally, maximal ratio combining is used to increase the gap between the fingerprint data, and the Weighted K-Nearest Neighbor (WKNN) algorithm is used to match the fingerprint data and estimate the location of the points to be located. The simulation results demonstrate the feasibility of the proposed method to achieve sub-meter accuracy in an NLOS environment. Full article
(This article belongs to the Special Issue New Advances in Navigation and Positioning Systems)
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