Multitarget Tracking by Particle Filtering Based on RSS Measurement in Wireless Sensor Networks

We propose an algorithm for multitarget tracking by particle filtering in wireless sensor networks based on received signal strength (RSS) measurement where we also localize a newly appearing target whose location and reference power are unknown. Therefore, the number, the reference power, and the i...

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Main Authors: Jaechan Lim, Uipil Chong
Format: Article
Language:English
Published: SAGE Publishing 2015-05-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1155/2015/837070
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spelling doaj-b0a2d2a9bc8f4a7bb3f2339caf5d43ad2020-11-25T03:19:21ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772015-05-011110.1155/2015/837070837070Multitarget Tracking by Particle Filtering Based on RSS Measurement in Wireless Sensor NetworksJaechan Lim0Uipil Chong1 Department of Creative IT Engineering/Future IT Innovation Laboratory, Pohang University of Science and Technology, Pohang 790-784, Republic of Korea School of Electrical Engineering, University of Ulsan, Ulsan 680-749, Republic of KoreaWe propose an algorithm for multitarget tracking by particle filtering in wireless sensor networks based on received signal strength (RSS) measurement where we also localize a newly appearing target whose location and reference power are unknown. Therefore, the number, the reference power, and the initial locations of targets are unknown in this problem. At the initial localization step, we apply approximate least squares (LS) method to roughly estimate the target location. After the initial location is estimated, we estimate the reference power. This is possible because we can use multiple number of measurements for estimating multiparameters. The proposed approach is particularly emphasized on the initialization step that completes the whole multitarget tracking system by particle filtering in a challenging scenario. The proposed approach is validated by computer simulations for its effectiveness.https://doi.org/10.1155/2015/837070
collection DOAJ
language English
format Article
sources DOAJ
author Jaechan Lim
Uipil Chong
spellingShingle Jaechan Lim
Uipil Chong
Multitarget Tracking by Particle Filtering Based on RSS Measurement in Wireless Sensor Networks
International Journal of Distributed Sensor Networks
author_facet Jaechan Lim
Uipil Chong
author_sort Jaechan Lim
title Multitarget Tracking by Particle Filtering Based on RSS Measurement in Wireless Sensor Networks
title_short Multitarget Tracking by Particle Filtering Based on RSS Measurement in Wireless Sensor Networks
title_full Multitarget Tracking by Particle Filtering Based on RSS Measurement in Wireless Sensor Networks
title_fullStr Multitarget Tracking by Particle Filtering Based on RSS Measurement in Wireless Sensor Networks
title_full_unstemmed Multitarget Tracking by Particle Filtering Based on RSS Measurement in Wireless Sensor Networks
title_sort multitarget tracking by particle filtering based on rss measurement in wireless sensor networks
publisher SAGE Publishing
series International Journal of Distributed Sensor Networks
issn 1550-1477
publishDate 2015-05-01
description We propose an algorithm for multitarget tracking by particle filtering in wireless sensor networks based on received signal strength (RSS) measurement where we also localize a newly appearing target whose location and reference power are unknown. Therefore, the number, the reference power, and the initial locations of targets are unknown in this problem. At the initial localization step, we apply approximate least squares (LS) method to roughly estimate the target location. After the initial location is estimated, we estimate the reference power. This is possible because we can use multiple number of measurements for estimating multiparameters. The proposed approach is particularly emphasized on the initialization step that completes the whole multitarget tracking system by particle filtering in a challenging scenario. The proposed approach is validated by computer simulations for its effectiveness.
url https://doi.org/10.1155/2015/837070
work_keys_str_mv AT jaechanlim multitargettrackingbyparticlefilteringbasedonrssmeasurementinwirelesssensornetworks
AT uipilchong multitargettrackingbyparticlefilteringbasedonrssmeasurementinwirelesssensornetworks
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