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Parametric Loop Division for 3D Localization in Wireless Sensor Networks

Localization in Wireless Sensor Networks (WSNs) has been an active topic for more than two decades. A variety of algorithms were proposed to improve the localization accuracy. However, they are either limited to two-dimensional (2D) space, or require specific sensor deployment for proper operations....

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Detalles Bibliográficos
Autores principales: Ahmad, Tanveer, Li, Xue Jun, Seet, Boon-Chong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5539484/
https://www.ncbi.nlm.nih.gov/pubmed/28737714
http://dx.doi.org/10.3390/s17071697
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author Ahmad, Tanveer
Li, Xue Jun
Seet, Boon-Chong
author_facet Ahmad, Tanveer
Li, Xue Jun
Seet, Boon-Chong
author_sort Ahmad, Tanveer
collection PubMed
description Localization in Wireless Sensor Networks (WSNs) has been an active topic for more than two decades. A variety of algorithms were proposed to improve the localization accuracy. However, they are either limited to two-dimensional (2D) space, or require specific sensor deployment for proper operations. In this paper, we proposed a three-dimensional (3D) localization scheme for WSNs based on the well-known parametric Loop division (PLD) algorithm. The proposed scheme localizes a sensor node in a region bounded by a network of anchor nodes. By iteratively shrinking that region towards its center point, the proposed scheme provides better localization accuracy as compared to existing schemes. Furthermore, it is cost-effective and independent of environmental irregularity. We provide an analytical framework for the proposed scheme and find its lower bound accuracy. Simulation results shows that the proposed algorithm provides an average localization accuracy of 0.89 m with a standard deviation of 1.2 m.
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spelling pubmed-55394842017-08-11 Parametric Loop Division for 3D Localization in Wireless Sensor Networks Ahmad, Tanveer Li, Xue Jun Seet, Boon-Chong Sensors (Basel) Article Localization in Wireless Sensor Networks (WSNs) has been an active topic for more than two decades. A variety of algorithms were proposed to improve the localization accuracy. However, they are either limited to two-dimensional (2D) space, or require specific sensor deployment for proper operations. In this paper, we proposed a three-dimensional (3D) localization scheme for WSNs based on the well-known parametric Loop division (PLD) algorithm. The proposed scheme localizes a sensor node in a region bounded by a network of anchor nodes. By iteratively shrinking that region towards its center point, the proposed scheme provides better localization accuracy as compared to existing schemes. Furthermore, it is cost-effective and independent of environmental irregularity. We provide an analytical framework for the proposed scheme and find its lower bound accuracy. Simulation results shows that the proposed algorithm provides an average localization accuracy of 0.89 m with a standard deviation of 1.2 m. MDPI 2017-07-24 /pmc/articles/PMC5539484/ /pubmed/28737714 http://dx.doi.org/10.3390/s17071697 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ahmad, Tanveer
Li, Xue Jun
Seet, Boon-Chong
Parametric Loop Division for 3D Localization in Wireless Sensor Networks
title Parametric Loop Division for 3D Localization in Wireless Sensor Networks
title_full Parametric Loop Division for 3D Localization in Wireless Sensor Networks
title_fullStr Parametric Loop Division for 3D Localization in Wireless Sensor Networks
title_full_unstemmed Parametric Loop Division for 3D Localization in Wireless Sensor Networks
title_short Parametric Loop Division for 3D Localization in Wireless Sensor Networks
title_sort parametric loop division for 3d localization in wireless sensor networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5539484/
https://www.ncbi.nlm.nih.gov/pubmed/28737714
http://dx.doi.org/10.3390/s17071697
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