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An Advanced Auxiliary Delay-Weight Particle Filter with Linear Computation Cost
We investigate the problem of tracking mobile targets in wireless sensor networks. We propose an advanced auxiliary delayed-weight particle filter algorithm (ADWPF). We make a deep study on the evolvement of particles and formally define the tree-like structure relationship among particles based on...
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Published in: | International journal of distributed sensor networks 2016-01, Vol.2016 (5), p.4535963 |
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container_title | International journal of distributed sensor networks |
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creator | Li, Chen Sun, Lin Zheng, Zengwei Chen, Dan |
description | We investigate the problem of tracking mobile targets in wireless sensor networks. We propose an advanced auxiliary delayed-weight particle filter algorithm (ADWPF). We make a deep study on the evolvement of particles and formally define the tree-like structure relationship among particles based on observations. Most importantly, we add some auxiliary particles to these structures formed by sampled particles in order to obtain more efficient structures. Based on the newly tree-like structures formed by auxiliary particles and sampled particles, we design a well efficient delayed-weight algorithm with linear computation cost. Experiment results demonstrate that our algorithm can greatly improve the tracking accuracy of a mobile target, compared with bootstrap filter, auxiliary particle filter, and another delayed-weight particle filter. |
doi_str_mv | 10.1155/2016/4535963 |
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We propose an advanced auxiliary delayed-weight particle filter algorithm (ADWPF). We make a deep study on the evolvement of particles and formally define the tree-like structure relationship among particles based on observations. Most importantly, we add some auxiliary particles to these structures formed by sampled particles in order to obtain more efficient structures. Based on the newly tree-like structures formed by auxiliary particles and sampled particles, we design a well efficient delayed-weight algorithm with linear computation cost. Experiment results demonstrate that our algorithm can greatly improve the tracking accuracy of a mobile target, compared with bootstrap filter, auxiliary particle filter, and another delayed-weight particle filter.</description><identifier>ISSN: 1550-1329</identifier><identifier>ISSN: 1550-1477</identifier><identifier>EISSN: 1550-1477</identifier><identifier>DOI: 10.1155/2016/4535963</identifier><language>eng</language><publisher>London, England: Hindawi Publishing Corporation</publisher><subject>Algorithms ; Applied research ; Computation ; Economic aspects ; Networks ; Remote sensors ; Sensors ; Target tracking ; Tracking ; Wireless networks ; Wireless sensor networks</subject><ispartof>International journal of distributed sensor networks, 2016-01, Vol.2016 (5), p.4535963</ispartof><rights>Copyright © 2016 Chen Li et al.</rights><rights>2016 Chen Li et al.</rights><rights>COPYRIGHT 2016 Sage Publications Ltd. (UK)</rights><rights>Copyright © 2016 Chen Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c494t-5e6345305504b95c141c994b6e8564a4f679ec4e0f07a6ff2fbbe1bef0e546fe3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/1790312408/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1790312408?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,25731,27901,27902,36989,36990,44566,75096</link.rule.ids></links><search><contributor>Barrero, Federico</contributor><creatorcontrib>Li, Chen</creatorcontrib><creatorcontrib>Sun, Lin</creatorcontrib><creatorcontrib>Zheng, Zengwei</creatorcontrib><creatorcontrib>Chen, Dan</creatorcontrib><title>An Advanced Auxiliary Delay-Weight Particle Filter with Linear Computation Cost</title><title>International journal of distributed sensor networks</title><description>We investigate the problem of tracking mobile targets in wireless sensor networks. 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Experiment results demonstrate that our algorithm can greatly improve the tracking accuracy of a mobile target, compared with bootstrap filter, auxiliary particle filter, and another delayed-weight particle filter.</description><subject>Algorithms</subject><subject>Applied research</subject><subject>Computation</subject><subject>Economic aspects</subject><subject>Networks</subject><subject>Remote sensors</subject><subject>Sensors</subject><subject>Target tracking</subject><subject>Tracking</subject><subject>Wireless networks</subject><subject>Wireless sensor networks</subject><issn>1550-1329</issn><issn>1550-1477</issn><issn>1550-1477</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>AFRWT</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNp9kk9v1DAQxSNEJcqWGx8gEhcQpPX_xMdooVBppXIAcbQcZ7zrVTZebKel3x4vWWhBFfLBo6ffPL-xpiheYnSOMecXBGFxwTjlUtAnxWmWUIVZXT_9XVMinxXPY9wiRAUR-LS4bsey7W_0aKAv2-mHG5wOd-V7GPRd9Q3cepPKzzokZwYoL92QIJS3Lm3KlRtBh3Lpd_sp6eT8mOuYzooTq4cIL473ovh6-eHL8lO1uv54tWxXlWGSpYqDoDkoyqlYJ7nBDBspWSeg4YJpZkUtwTBAFtVaWEts1wHuwCLgTFigi-Jq9u293qp9cLscW3nt1C_Bh7U6plZSCo572ktCMGuAdcRoRJq-1rVkff6JRfF69toH_32CmNTORQPDoEfwU1S4wQJxQhue0Vf_oFs_hTFPqnAtEcWEoeaeWuv8vhutT0Gbg6lqOZJMSIxpps4fofLpYeeMH8G6rP_V8G5uMMHHGMD-mRsjdVgAdVgAdVyAjL-Z8ajX8CDn4-zbmd24sde37v_OPwGD7be3</recordid><startdate>20160101</startdate><enddate>20160101</enddate><creator>Li, Chen</creator><creator>Sun, Lin</creator><creator>Zheng, Zengwei</creator><creator>Chen, Dan</creator><general>Hindawi Publishing Corporation</general><general>SAGE Publications</general><general>Sage Publications Ltd. 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We propose an advanced auxiliary delayed-weight particle filter algorithm (ADWPF). We make a deep study on the evolvement of particles and formally define the tree-like structure relationship among particles based on observations. Most importantly, we add some auxiliary particles to these structures formed by sampled particles in order to obtain more efficient structures. Based on the newly tree-like structures formed by auxiliary particles and sampled particles, we design a well efficient delayed-weight algorithm with linear computation cost. Experiment results demonstrate that our algorithm can greatly improve the tracking accuracy of a mobile target, compared with bootstrap filter, auxiliary particle filter, and another delayed-weight particle filter.</abstract><cop>London, England</cop><pub>Hindawi Publishing Corporation</pub><doi>10.1155/2016/4535963</doi><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Applied research Computation Economic aspects Networks Remote sensors Sensors Target tracking Tracking Wireless networks Wireless sensor networks |
title | An Advanced Auxiliary Delay-Weight Particle Filter with Linear Computation Cost |
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