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Emerging Advances in Wireless Positioning and Location-Based Services
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Emerging Advances in Wireless Positioning and Location-Based Services

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Navigation and Positioning".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 4759

Special Issue Editors

Dr. Xi Chen

E-Mail Website
Guest Editor
Aerospace Information Technology Research Institute of Aeronautics and Astronautics, Tsinghua University, Shuangqing Rd, Haidian District, Beijing 100190, China
Interests: integrated satellite communication and navigation; massive signals of opportunity positioning
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Xingxing Li

E-Mail Website
Guest Editor
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
Interests: GPS; GNSS precise positioning and orbit determination; GNSS data processing and multisensor fusion; GNSS seismology; GNSS meteorology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, there has been significant and swift progress in the development of intelligent artifacts such as robots, UAVs, and autonomous cars. These intelligent artifacts heavily depend on positioning, navigation, and timing (PNT) information. Although GNSS-based satellite positioning remains dominant, there are several emerging technologies that show great promise for enhancing accuracy and reliability, such as integrated satellite positioning in low-Earth-orbit satellite communication megaconstellations, signal-of-opportunity positioning, and cooperative positioning. This Special Issue focuses on highlighting the recent advancements in wireless positioning, multi-sensor fusion, location-based services, and other location sensors, aiming to provide improved precision and reliability for various applications.

Dr. Xi Chen
Prof. Dr. Xingxing Li
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. Sensors 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 2600 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

  • satellite positioning
  • LEO positioning, navigation, and timing
  • integrated positioning, navigation, and timing in satellite communication constellations
  • precise point positioning
  • GNSS
  • assured PNT with satellite positioning
  • location-based service
  • satellite signal-of-opportunity positioning
  • multi-sensor fusion with GNSS, Lidar, vision, and IMU
  • satellite positioning for robots, UAVs, and autonomous cars
  • GNSS augmentation
  • GNSS interference detection and localization

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Published Papers (4 papers)

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Research

17 pages, 7941 KiB  
Article
Visual Localization Domain for Accurate V-SLAM from Stereo Cameras
by Eleonora Di Salvo, Sara Bellucci, Valeria Celidonio, Ilaria Rossini, Stefania Colonnese and Tiziana Cattai
Sensors 2025, 25(3), 739; https://doi.org/10.3390/s25030739 - 26 Jan 2025
Viewed by 754
Abstract
Trajectory estimation from stereo image sequences remains a fundamental challenge in Visual Simultaneous Localization and Mapping (V-SLAM). To address this, we propose a novel approach that focuses on the identification and matching of keypoints within a transformed domain that emphasizes visually significant features. [...] Read more.
Trajectory estimation from stereo image sequences remains a fundamental challenge in Visual Simultaneous Localization and Mapping (V-SLAM). To address this, we propose a novel approach that focuses on the identification and matching of keypoints within a transformed domain that emphasizes visually significant features. Specifically, we propose to perform V-SLAM in a VIsual Localization Domain (VILD), i.e., a domain where visually relevant feature are suitably represented for analysis and tracking. This transformed domain adheres to information-theoretic principles, enabling a maximum likelihood estimation of rotation, translation, and scaling parameters by minimizing the distance between the coefficients of the observed image and those of a reference template. The transformed coefficients are obtained from the output of specialized Circular Harmonic Function (CHF) filters of varying orders. Leveraging this property, we employ a first-order approximation of the image-series representation, directly computing the first-order coefficients through the application of first-order CHF filters. The proposed VILD provides a theoretically grounded and visually relevant representation of the image. We utilize VILD for point matching and tracking across the stereo video sequence. The experimental results on real-world video datasets demonstrate that integrating visually-driven filtering significantly improves trajectory estimation accuracy compared to traditional tracking performed in the spatial domain. Full article
(This article belongs to the Special Issue Emerging Advances in Wireless Positioning and Location-Based Services)
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27 pages, 11525 KiB  
Article
Mobile Robot Positioning with Wireless Fidelity Fingerprinting and Explainable Artificial Intelligence
by Hüseyin Abacı and Ahmet Çağdaş Seçkin
Sensors 2024, 24(24), 7943; https://doi.org/10.3390/s24247943 - 12 Dec 2024
Viewed by 877
Abstract
Wireless Fidelity (Wi-Fi) based positioning has gained popularity for accurate indoor robot positioning in indoor navigation. In daily life, it is a low-cost solution because Wi-Fi infrastructure is already installed in many indoor areas. In addition, unlike the Global Navigation Satellite System (GNSS), [...] Read more.
Wireless Fidelity (Wi-Fi) based positioning has gained popularity for accurate indoor robot positioning in indoor navigation. In daily life, it is a low-cost solution because Wi-Fi infrastructure is already installed in many indoor areas. In addition, unlike the Global Navigation Satellite System (GNSS), Wi-Fi is more suitable for use indoors because signal blocking, attenuation, and reflection restrictions create a unique pattern in places with many Wi-Fi transmitters, and more precise positioning can be performed than GNSS. This paper proposes a machine learning-based method for Wi-Fi-enabled robot positioning in indoor environments. The contributions of this research include comprehensive 3D position estimation, utilization of existing Wi-Fi infrastructure, and a carefully collected dataset for evaluation. The results indicate that the AdaBoost algorithm attains a notable level of accuracy, utilizing the dBm signal strengths from Wi-Fi access points distributed throughout a four-floor building. The mean average error (MAE) values obtained in three axes with the Adaptive Boosting algorithm are 0.044 on the x-axis, 0.063 on the y-axis, and 0.003 m on the z-axis, respectively. In this study, the importance of various Wi-Fi access points was examined with explainable artificial intelligence methods, and the positioning performances obtained by using data from a smaller number of access points were examined. As a result, even when positioning was conducted with only seven selected Wi-Fi access points, the MAE value was found to be 0.811 for the x-axis, 0.492 for the y-axis, and 0.134 for the Z-axis, respectively. Full article
(This article belongs to the Special Issue Emerging Advances in Wireless Positioning and Location-Based Services)
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22 pages, 8030 KiB  
Article
A Study on a Radio Source Location Estimation System Using High Altitude Platform Stations (HAPS)
by Yuta Furuse and Gia Khanh Tran
Sensors 2024, 24(17), 5803; https://doi.org/10.3390/s24175803 - 6 Sep 2024
Cited by 2 | Viewed by 1144
Abstract
Currently, there is a system in Japan to detect illegal radio transmitting sources, known as the DEURAS system. Even though crackdowns on illegal radio stations are conducted on a regular basis every year, the number of illegal emission cases still tends to increase, [...] Read more.
Currently, there is a system in Japan to detect illegal radio transmitting sources, known as the DEURAS system. Even though crackdowns on illegal radio stations are conducted on a regular basis every year, the number of illegal emission cases still tends to increase, as ordinary citizens are now able to handle advanced wireless communication technologies, e.g., via software-defined radio. However, the current surveillance system may not be able to accurately detect the source in areas where large buildings are densely packed, such as urban areas, due to the effects of reflected waves. Therefore, in this study, we proposed a system for estimating the location of the source of transmission using a high-flying unmanned aerial vehicle called HAPS. The simulation results using numerical analysis software show that the proposed system can estimate the location of the source over a wider area and with higher accuracy than conventional monitoring systems. Full article
(This article belongs to the Special Issue Emerging Advances in Wireless Positioning and Location-Based Services)
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23 pages, 13894 KiB  
Article
Analysis of Post-Processed Pseudorange-Based Point Positioning with Different Data Sources for the Current Galileo Constellations
by Jiantao Zhang and Weiwei Li
Sensors 2024, 24(8), 2472; https://doi.org/10.3390/s24082472 - 12 Apr 2024
Cited by 1 | Viewed by 1295
Abstract
The Galileo satellite navigation system now provides initial services. With further satellite launches, the performance of Galileo will gradually improve, and new services will be introduced. This study aims to provide a comprehensive analysis of Galileo Single Point Positioning (SPP) using different broadcast [...] Read more.
The Galileo satellite navigation system now provides initial services. With further satellite launches, the performance of Galileo will gradually improve, and new services will be introduced. This study aims to provide a comprehensive analysis of Galileo Single Point Positioning (SPP) using different broadcast ephemeris data sources. This study investigates the completeness of Galileo navigation message records from different institutions. The results show that IGS provides the best completeness across different data sources (ECR > 70%), while IGN exhibits the lowest completeness. Analyze the proportions of different data sources within the Galileo navigation message in the broadcast ephemeris files provided by IGS during the study period. The proportions of FNAV_258, INAV_513, INAV_516, and INAV_517 during the study period are 25.83%, 24.76%, 23.61%, and 25.80%, respectively, suggesting better data completeness for FNAV_258 and INAV_517 and poorer completeness for INAV_513 and INAV_516. Finally, this study explores SPP solutions for GPS and Galileo systems using different data sources. The results indicate that a higher ECR corresponds to better positioning performance. Although GPS exhibits smaller error fluctuations and smoother positioning results, Galileo’s SPP positioning accuracy surpasses that of GPS. The introduction of dual-frequency observations effectively reduces data dispersion and enhances vertical positioning accuracy. Full article
(This article belongs to the Special Issue Emerging Advances in Wireless Positioning and Location-Based Services)
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