Multi-source localization with binary sensor networks

A new multi-source detection model was proposed based on Neyman-Pearson criterion to reduce the computa-tional complexity caused in the multi-source localization.The Fisher criterion was employed to divide sensors into two parts,where two sources were present and each part corresponds to one of the...

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Main Authors: CHENG Long1, WU Cheng-dong1, ZHANG Yun-zhou1, JIA Zi-xi1, JI Peng1
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2011-01-01
Series:Tongxin xuebao
Subjects:
Online Access:http://www.joconline.com.cn/zh/article/74419751/
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author CHENG Long1
WU Cheng-dong1
ZHANG Yun-zhou1
JIA Zi-xi1
JI Peng1
author_facet CHENG Long1
WU Cheng-dong1
ZHANG Yun-zhou1
JIA Zi-xi1
JI Peng1
author_sort CHENG Long1
collection DOAJ
description A new multi-source detection model was proposed based on Neyman-Pearson criterion to reduce the computa-tional complexity caused in the multi-source localization.The Fisher criterion was employed to divide sensors into two parts,where two sources were present and each part corresponds to one of the sources.The WSNAP(weighted subtract on negative add on positive) multi-source location algorithm was applied to localize the multiple sources.The simulation results show that Fisher criterion is able to divide the alarmed sensor into two parts with relatively higher accuracy.The proposed WSNAP has better estimation accuracy than AP(add positive) algorithm and CE(centroid estimator) algorithm under the circumstance of lower computation complexity.Finally,the results are verified using the database of distributed wireless sensor networks.
format Article
id doaj-art-0d683a2420174e8d8c5e6a468a1cd7b8
institution Kabale University
issn 1000-436X
language zho
publishDate 2011-01-01
publisher Editorial Department of Journal on Communications
record_format Article
series Tongxin xuebao
spelling doaj-art-0d683a2420174e8d8c5e6a468a1cd7b82025-01-14T08:15:32ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2011-01-013215816574419751Multi-source localization with binary sensor networksCHENG Long1WU Cheng-dong1ZHANG Yun-zhou1JIA Zi-xi1JI Peng1A new multi-source detection model was proposed based on Neyman-Pearson criterion to reduce the computa-tional complexity caused in the multi-source localization.The Fisher criterion was employed to divide sensors into two parts,where two sources were present and each part corresponds to one of the sources.The WSNAP(weighted subtract on negative add on positive) multi-source location algorithm was applied to localize the multiple sources.The simulation results show that Fisher criterion is able to divide the alarmed sensor into two parts with relatively higher accuracy.The proposed WSNAP has better estimation accuracy than AP(add positive) algorithm and CE(centroid estimator) algorithm under the circumstance of lower computation complexity.Finally,the results are verified using the database of distributed wireless sensor networks.http://www.joconline.com.cn/zh/article/74419751/wireless sensor networksmulti-source localizationbinary sensorNeyman-Pearson criterionFisher criterion
spellingShingle CHENG Long1
WU Cheng-dong1
ZHANG Yun-zhou1
JIA Zi-xi1
JI Peng1
Multi-source localization with binary sensor networks
Tongxin xuebao
wireless sensor networks
multi-source localization
binary sensor
Neyman-Pearson criterion
Fisher criterion
title Multi-source localization with binary sensor networks
title_full Multi-source localization with binary sensor networks
title_fullStr Multi-source localization with binary sensor networks
title_full_unstemmed Multi-source localization with binary sensor networks
title_short Multi-source localization with binary sensor networks
title_sort multi source localization with binary sensor networks
topic wireless sensor networks
multi-source localization
binary sensor
Neyman-Pearson criterion
Fisher criterion
url http://www.joconline.com.cn/zh/article/74419751/
work_keys_str_mv AT chenglong1 multisourcelocalizationwithbinarysensornetworks
AT wuchengdong1 multisourcelocalizationwithbinarysensornetworks
AT zhangyunzhou1 multisourcelocalizationwithbinarysensornetworks
AT jiazixi1 multisourcelocalizationwithbinarysensornetworks
AT jipeng1 multisourcelocalizationwithbinarysensornetworks