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Selected Papers from 13th International Conference on Localization and GNSS 2023 (ICL-GNSS 2023)

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

Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 10578

Special Issue Editor

Prof. Dr. Jari Nurmi

E-Mail Website
Guest Editor
Electrical Engineering, Tampere University, Tampere, Finland
Interests: GNSS receiver architecture and implementation; multi-technology positioning; software-defined radio for communications and positioning; cognitive and cooperative positioning; IoT and embedded systems; reconfigurable and adaptable systems; approximate computing in particular in the receiver baseband domain
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The 13th International Conference on Localization and GNSS (ICL-GNSS 2023) (https://events.tuni.fi/icl-gnss2023/) will be held on 6–8 June 2023 in Castellon, Spain.

Reliable navigation and positioning are becoming essential in applications of the IoT, including in industry and logistic applications, in smart city environments, for safety-critical purposes, and in public services and consumer products, in order to guarantee transparent, efficient, and reliable workflows. A robust localization solution is urgently required, which will be continuously available, regardless of whether it is implemented outdoors or indoors, or on different platforms. ICL-GNSS addresses the latest research on wireless and satellite-based positioning techniques for providing reliable and accurate position information with low latency. Emphasis is placed on the design of mass-market navigation receivers and related tools and methodologies; however, many types of sensing devices, wireless systems with localization capabilities, and location-aware applications are within the scope of the Special Issue.

The authors of the selected papers, related to sensors, from the conference, are invited to submit extended versions of their original papers.

Prof. Dr. Jari Nurmi
Guest Editor

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.

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Published Papers (3 papers)

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Research

17 pages, 2320 KiB  
Article
LSTM-Based GNSS Localization Using Satellite Measurement Features Jointly with Pseudorange Residuals
by Ibrahim Sbeity, Christophe Villien, Benoît Denis and Elena Veronica Belmega
Sensors 2024, 24(3), 833; https://doi.org/10.3390/s24030833 - 27 Jan 2024
Viewed by 2966
Abstract
In the Global Navigation Satellite System (GNSS) context, the growing number of available satellites has led to many challenges when it comes to choosing the most-accurate pseudorange contributions, given the strong impact of biased measurements on positioning accuracy, particularly in single-epoch scenarios. This [...] Read more.
In the Global Navigation Satellite System (GNSS) context, the growing number of available satellites has led to many challenges when it comes to choosing the most-accurate pseudorange contributions, given the strong impact of biased measurements on positioning accuracy, particularly in single-epoch scenarios. This work leverages the potential of machine learning in predicting linkwise measurement quality factors and, hence, optimize measurement weighting. For this purpose, we used a customized matrix composed of heterogeneous features such as conditional pseudorange residuals and per-link satellite metrics (e.g., carrier-to-noise-power-density ratio and its empirical statistics, satellite elevation, carrier phase lock time). This matrix is then fed as an input to a long short-term memory (LSTM) deep neural network capable of exploiting the hidden correlations between these features relevant to positioning, leading to the predictions of efficient measurement weights. Our extensive experimental results on real data, obtained from extensive field measurements, demonstrate the high potential of our proposed solution, which is able to outperform traditional measurement weighting and selection strategies from the state-of-the-art. In addition, we included detailed illustrations based on representative sessions to provide a concrete understanding of the significant gains of our approach, particularly in strongly GNSS-challenged operating conditions. Full article
(This article belongs to the Special Issue Selected Papers from 13th International Conference on Localization and GNSS 2023 (ICL-GNSS 2023))
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22 pages, 983 KiB  
Article
Hard SyDR: A Benchmarking Environment for Global Navigation Satellite System Algorithms
by Antoine Grenier, Jie Lei, Hans Jakob Damsgaard, Enrique S. Quintana-Ortí, Aleksandr Ometov, Elena Simona Lohan and Jari Nurmi
Sensors 2024, 24(2), 409; https://doi.org/10.3390/s24020409 - 9 Jan 2024
Viewed by 5350
Abstract
A Global Navigation Satellite System (GNSS) is widely used today for both positioning and timing purposes. Many distinct receiver chips are available as Application-Specific Integrated Circuit (ASIC)s off-the-shelf, each tailored to the requirements of various applications. These chips deliver good performance and low [...] Read more.
A Global Navigation Satellite System (GNSS) is widely used today for both positioning and timing purposes. Many distinct receiver chips are available as Application-Specific Integrated Circuit (ASIC)s off-the-shelf, each tailored to the requirements of various applications. These chips deliver good performance and low energy consumption but offer customers little-to-no transparency about their internal features. This prevents modification, research in GNSS processing chain enhancement (e.g., application of Approximate Computing (AxC) techniques), and design space exploration to find the optimal receiver for a use case. In this paper, we review the GNSS processing chain using SyDR, our open-source GNSS Software-Defined Radio (SDR) designed for algorithm benchmarking, and highlight the limitations of a software-only environment. In return, we propose an evolution to our system, called Hard SyDR to become closer to the hardware layer and access new Key Performance Indicator (KPI)s, such as power/energy consumption and resource utilization. We use High-Level Synthesis (HLS) and the PYNQ platform to ease our development process and provide an overview of their advantages/limitations in our project. Finally, we evaluate the foreseen developments, including how this work can serve as the foundation for an exploration of AxC techniques in future low-power GNSS receivers. Full article
(This article belongs to the Special Issue Selected Papers from 13th International Conference on Localization and GNSS 2023 (ICL-GNSS 2023))
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15 pages, 1575 KiB  
Article
An Experimental Performance Assessment of Galileo OSNMA
by Toni Hammarberg, José M. Vallet García, Jarno N. Alanko and M. Zahidul H. Bhuiyan
Sensors 2024, 24(2), 404; https://doi.org/10.3390/s24020404 - 9 Jan 2024
Cited by 2 | Viewed by 1450
Abstract
We present Galileo Open Service Navigation Message Authentication (OSNMA) observed operational information and key performance indicators (KPIs) from the analysis of a ten-day-long dataset collected in static open-sky conditions in southern Finland and using our in-house-developed OSNMA implementation. In particular, we present a [...] Read more.
We present Galileo Open Service Navigation Message Authentication (OSNMA) observed operational information and key performance indicators (KPIs) from the analysis of a ten-day-long dataset collected in static open-sky conditions in southern Finland and using our in-house-developed OSNMA implementation. In particular, we present a timeline with authentication-related events, such as authentication status and type, dropped navigation pages, and failed cyclic redundancy checks. We also report other KPIs, such as the number of simultaneously authenticated satellites over time, time to first authenticated fix, and percentage of authenticated fixes, and we evaluate the accuracy of the authenticated position solution. We also study how satellite visibility affects these figures. Finally, we analyze situations where it was not possible to reach an authenticated fix, and offer our findings on the observed patterns. Full article
(This article belongs to the Special Issue Selected Papers from 13th International Conference on Localization and GNSS 2023 (ICL-GNSS 2023))
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