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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Format: | Article |
Language: | zho |
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Editorial Department of Journal on Communications
2011-01-01
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Series: | Tongxin xuebao |
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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 |