Improved sequence-based localization applied in coal mine

Complex geographical environment brings tremendous challenges to get information of localization in underground coal mines. Sequence-based localization is a simple method; without calculating distance during the positioning stage in real time, this method uses the received signal strength indication...

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Main Authors: Mingzhi Song, Jiansheng Qian
Format: Article
Language:English
Published: Wiley 2016-11-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1177/1550147716669615
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author Mingzhi Song
Jiansheng Qian
author_facet Mingzhi Song
Jiansheng Qian
author_sort Mingzhi Song
collection DOAJ
description Complex geographical environment brings tremendous challenges to get information of localization in underground coal mines. Sequence-based localization is a simple method; without calculating distance during the positioning stage in real time, this method uses the received signal strength indication matched degree between unknown node and regions to locate. However, sequence-based localization has a great issue on poor marginal nodes localization. Sequence–centroid localization contributes to improving this issue, but the location error on the boundary of whole area is unsatisfactory as well. This article proposes an improved sequence-based localization method which is integrated with quantum-behaved particle swarm optimization, as quantum-behaved particle swarm optimization makes good use of the search performance of global optimal solution. In our simulation, we consider that ZigBee devices can be used to construct wireless sensor networks and locate personnel location. The results prove that the improved sequence-based localization algorithm provides comparable accuracy than sequence-based localization.
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institution DOAJ
issn 1550-1477
language English
publishDate 2016-11-01
publisher Wiley
record_format Article
series International Journal of Distributed Sensor Networks
spelling doaj-art-86fcc8f896fc42bab870004cee348e122025-08-20T03:07:16ZengWileyInternational Journal of Distributed Sensor Networks1550-14772016-11-011210.1177/1550147716669615Improved sequence-based localization applied in coal mineMingzhi SongJiansheng QianComplex geographical environment brings tremendous challenges to get information of localization in underground coal mines. Sequence-based localization is a simple method; without calculating distance during the positioning stage in real time, this method uses the received signal strength indication matched degree between unknown node and regions to locate. However, sequence-based localization has a great issue on poor marginal nodes localization. Sequence–centroid localization contributes to improving this issue, but the location error on the boundary of whole area is unsatisfactory as well. This article proposes an improved sequence-based localization method which is integrated with quantum-behaved particle swarm optimization, as quantum-behaved particle swarm optimization makes good use of the search performance of global optimal solution. In our simulation, we consider that ZigBee devices can be used to construct wireless sensor networks and locate personnel location. The results prove that the improved sequence-based localization algorithm provides comparable accuracy than sequence-based localization.https://doi.org/10.1177/1550147716669615
spellingShingle Mingzhi Song
Jiansheng Qian
Improved sequence-based localization applied in coal mine
International Journal of Distributed Sensor Networks
title Improved sequence-based localization applied in coal mine
title_full Improved sequence-based localization applied in coal mine
title_fullStr Improved sequence-based localization applied in coal mine
title_full_unstemmed Improved sequence-based localization applied in coal mine
title_short Improved sequence-based localization applied in coal mine
title_sort improved sequence based localization applied in coal mine
url https://doi.org/10.1177/1550147716669615
work_keys_str_mv AT mingzhisong improvedsequencebasedlocalizationappliedincoalmine
AT jianshengqian improvedsequencebasedlocalizationappliedincoalmine