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Target Localization in Wireless Sensor Networks – Current Trends and Future Challenges

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: closed (30 March 2023) | Viewed by 5011

Special Issue Editors


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Guest Editor
Department of Computer Engineering, Universidade Lusófona de Humanidades e Tecnologias, Portugal
Interests: target localization; non-convex optimization
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
1. COPELABS, Universidade Lusófona de Humanidades e Tecnologias, Campo Grande 376, 1749-024 Lisboa, Portugal
2. VALORIZA, Instituto Politécnico de Portalegre, Campus Politécnico n.10, 7300-555 Portalegre, Portugal
Interests: sensors networks; applied mathematics; computer science; electrical engineering; optimization algorithms; electronics and communication engineering; localization algorithms; analog and digital hardware design; Internet of Things; embedded design; artificial intelligence; computer architectures
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Instituto de Telecomunicações, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
Interests: wireless sensor networks; cognitive radio; source localization; PAPR reduction; MIMO communications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The emerging fifth generation (5G) network will have the capacity to join myriads of miscellaneous devices (users, objects, and vehicles) into a single network (of sensors), known as the Internet-of-Things (IoT). The key issue in many sensor network applications (e.g., user-personalized location-based services, location-aware interference mitigation, power, and latency optimized end-to-end communications) is to accurately determine the position of a source. For decades, the global positioning system (GPS) has been the paramount scheme for positioning, but it is often impractical to equip each sensor with a GPS chip, not to mention the constrained service in urban and indoor environments. Therefore, alternative (terrestrial) solutions have begun to garner attention.

Previously, advances in wireless localization and communication techniques have been performed separately. This is expected to change in 5G networks, where large bandwidths and dense access point deployment are foreseen to enable higher localization accuracy with low energy consumption. Although such accomplishments favor all participants in the localization chain (end users, network operators, and location service providers), they might raise security issues. This is because most localization systems are designed for harmless settings without the presence of adversaries. This makes them vulnerable to threats from interference, attacks, or even unintentional errors (malfunctions). Therefore, an additional requirement for future localization systems is that the estimation process is carried out securely in order to avoid disastrous consequences with possible casualties.

Topics of Interest

  • 5G and beyond wireless localization;
  • Machine Learning and Artificial Intelligence for localization systems;
  • Security, data privacy, and trust of localization systems;
  • UAV-Assisted localization;
  • Novel applications of localization and tracking;
  • Software/Hardware codesign for localization systems;
  • Edge and fog computing for localization Systems;
  • Internet-of-Things based localization Systems;
  • Energy-efficient localization and tracking;
  • Localization systems based on low power networks;
  • Single and multiple target localization;
  • Range-based and range-free localization;
  • Acoustic and underwater localization;
  • Light-based localization;
  • Hybrid localization;
  • Collaborative localization and mapping;
  • Distributed localization;
  • Benchmarking localization performance in wireless networks;
  • Target tracking;
  • UAV navigation and Wi-Fly networks;
  • Localization based on stochastic geometry.

Prof. Slavisa Tomic
Dr. Sergio Correia
Prof. Dr. Marko Beko
Guest Editors

Manuscript Submission Information

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Published Papers (2 papers)

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Research

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20 pages, 4584 KiB  
Article
Mobile-BAT—A Novel Ultra-Low Power Wildlife Tracking System
by Stefan Erhardt, Martin Koch, Andreas Kiefer, Michael Veith, Robert Weigel and Alexander Koelpin
Sensors 2023, 23(11), 5236; https://doi.org/10.3390/s23115236 - 31 May 2023
Viewed by 1730
Abstract
We introduce a novel ultra-low power system for tracking animal movements over long periods with an unprecedented high-temporal-resolution. The localization principle is based on the detection of cellular base stations using a miniaturized software-defined radio, weighing 2.0 g, including the battery, and having [...] Read more.
We introduce a novel ultra-low power system for tracking animal movements over long periods with an unprecedented high-temporal-resolution. The localization principle is based on the detection of cellular base stations using a miniaturized software-defined radio, weighing 2.0 g, including the battery, and having a size equivalent to two stacked 1-euro cent coins. Therefore, the system is small and lightweight enough to be deployed on small, wide-ranging, or migrating animals, such as European bats, for movement analysis with an unprecedented spatiotemporal resolution. The position estimation relies on a post-processing probabilistic RF pattern-matching method based on the acquired base stations and power levels. In several field tests, the system has been successfully verified, and a run-time of close to one year has been demonstrated. Full article
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Review

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37 pages, 1669 KiB  
Review
Swarm Optimization for Energy-Based Acoustic Source Localization: A Comprehensive Study
by João Fé, Sérgio D. Correia, Slavisa Tomic and Marko Beko
Sensors 2022, 22(5), 1894; https://doi.org/10.3390/s22051894 - 28 Feb 2022
Cited by 4 | Viewed by 2054
Abstract
In the last decades, several swarm-based optimization algorithms have emerged in the scientific literature, followed by a massive increase in terms of their fields of application. Most of the studies and comparisons are restricted to high-level languages (such as MATLAB®) and [...] Read more.
In the last decades, several swarm-based optimization algorithms have emerged in the scientific literature, followed by a massive increase in terms of their fields of application. Most of the studies and comparisons are restricted to high-level languages (such as MATLAB®) and testing methods on classical benchmark mathematical functions. Specifically, the employment of swarm-based methods for solving energy-based acoustic localization problems is still in its inception and has not yet been extensively studied. As such, the present work marks the first comprehensive study of swarm-based optimization algorithms applied to the energy-based acoustic localization problem. To this end, a total of 10 different algorithms were subjected to an extensive set of simulations with the following aims: (1) to compare the algorithms’ convergence performance and recognize novel, promising methods for solving the problem of interest; (2) to validate the importance (in convergence speed) of an intelligent swarm initialization for any swarm-based algorithm; (3) to analyze the methods’ time efficiency when implemented in low-level languages and when executed on embedded processors. The obtained results disclose the high potential of some of the considered swarm-based optimization algorithms for the problem under study, showing that these methods can accurately locate acoustic sources with low latency and bandwidth requirements, making them highly attractive for edge computing paradigms. Full article
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