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A Passive Tracking System Based on Geometric Constraints in Adaptive Wireless Sensor Networks †

Target tracking technologies in wireless sensor network (WSNs) environments fall into two categories: active and passive schemes. Unlike with the active positioning schemes, in which the targets are required to hold cooperative devices, the research on passive tracking, i.e., tracking device-free ta...

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Autores principales: Zhou, Biao, Ahn, Deockhyeon, Lee, Jungpyo, Sun, Chao, Ahmed, Sabbir, Kim, Youngok
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6209868/
https://www.ncbi.nlm.nih.gov/pubmed/30274276
http://dx.doi.org/10.3390/s18103276
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author Zhou, Biao
Ahn, Deockhyeon
Lee, Jungpyo
Sun, Chao
Ahmed, Sabbir
Kim, Youngok
author_facet Zhou, Biao
Ahn, Deockhyeon
Lee, Jungpyo
Sun, Chao
Ahmed, Sabbir
Kim, Youngok
author_sort Zhou, Biao
collection PubMed
description Target tracking technologies in wireless sensor network (WSNs) environments fall into two categories: active and passive schemes. Unlike with the active positioning schemes, in which the targets are required to hold cooperative devices, the research on passive tracking, i.e., tracking device-free targets, has recently showed promise. In the WSN, device-free targets can be tracked by sensing radio frequency tomography (RFT) on the line-of-sight links (LOSLs). In this paper, we propose a passive tracking scheme exploiting both adaptive-networking LOSL webs and geometric constraint methodology for tracking single targets, as well as multiple targets. Regarding fundamental knowledge, we firstly explore the spatial diversity technique for RFT detection in realistic situations. Then, we analyze the power consumption of the WSN and propose an adaptive networking scheme for the purpose of energy conservation. Instead of maintaining a fixed LOSL density, the proposed scheme can adaptively adjust the networking level to save energy while guaranteeing tracking accuracy. The effectiveness of the proposed scheme is evaluated with computer simulations. According to the results, it is observed that the proposed scheme can sufficiently reduce power consumption, while providing qualified tracking performance.
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spelling pubmed-62098682018-11-02 A Passive Tracking System Based on Geometric Constraints in Adaptive Wireless Sensor Networks † Zhou, Biao Ahn, Deockhyeon Lee, Jungpyo Sun, Chao Ahmed, Sabbir Kim, Youngok Sensors (Basel) Article Target tracking technologies in wireless sensor network (WSNs) environments fall into two categories: active and passive schemes. Unlike with the active positioning schemes, in which the targets are required to hold cooperative devices, the research on passive tracking, i.e., tracking device-free targets, has recently showed promise. In the WSN, device-free targets can be tracked by sensing radio frequency tomography (RFT) on the line-of-sight links (LOSLs). In this paper, we propose a passive tracking scheme exploiting both adaptive-networking LOSL webs and geometric constraint methodology for tracking single targets, as well as multiple targets. Regarding fundamental knowledge, we firstly explore the spatial diversity technique for RFT detection in realistic situations. Then, we analyze the power consumption of the WSN and propose an adaptive networking scheme for the purpose of energy conservation. Instead of maintaining a fixed LOSL density, the proposed scheme can adaptively adjust the networking level to save energy while guaranteeing tracking accuracy. The effectiveness of the proposed scheme is evaluated with computer simulations. According to the results, it is observed that the proposed scheme can sufficiently reduce power consumption, while providing qualified tracking performance. MDPI 2018-09-29 /pmc/articles/PMC6209868/ /pubmed/30274276 http://dx.doi.org/10.3390/s18103276 Text en © 2018 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
Zhou, Biao
Ahn, Deockhyeon
Lee, Jungpyo
Sun, Chao
Ahmed, Sabbir
Kim, Youngok
A Passive Tracking System Based on Geometric Constraints in Adaptive Wireless Sensor Networks †
title A Passive Tracking System Based on Geometric Constraints in Adaptive Wireless Sensor Networks †
title_full A Passive Tracking System Based on Geometric Constraints in Adaptive Wireless Sensor Networks †
title_fullStr A Passive Tracking System Based on Geometric Constraints in Adaptive Wireless Sensor Networks †
title_full_unstemmed A Passive Tracking System Based on Geometric Constraints in Adaptive Wireless Sensor Networks †
title_short A Passive Tracking System Based on Geometric Constraints in Adaptive Wireless Sensor Networks †
title_sort passive tracking system based on geometric constraints in adaptive wireless sensor networks †
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6209868/
https://www.ncbi.nlm.nih.gov/pubmed/30274276
http://dx.doi.org/10.3390/s18103276
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