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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2015-05-01
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Series: | International Journal of Distributed Sensor Networks |
Online Access: | https://doi.org/10.1155/2015/837070 |
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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 |
_version_ |
1724622910947065856 |