Decentralized Cooperative TOA/AOA Target Tracking for Hierarchical Wireless Sensor Networks

This paper proposes a distributed method for cooperative target tracking in hierarchical wireless sensor networks. The concept of leader-based information processingis conducted to achieve object positioning, considering a cluster-based network topology. Random timers and local information are appli...

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Main Authors: Chih-Yu Wen, Ying-Chih Chen
Format: Article
Language:English
Published: MDPI AG 2012-11-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/12/11/15308
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author Chih-Yu Wen
Ying-Chih Chen
author_facet Chih-Yu Wen
Ying-Chih Chen
author_sort Chih-Yu Wen
collection DOAJ
description This paper proposes a distributed method for cooperative target tracking in hierarchical wireless sensor networks. The concept of leader-based information processingis conducted to achieve object positioning, considering a cluster-based network topology. Random timers and local information are applied to adaptively select a sub-cluster for thelocalization task. The proposed energy-efficient tracking algorithm allows each sub-clustermember to locally estimate the target position with a Bayesian filtering framework and a neural networking model, and further performs estimation fusion in the leader node with the covariance intersection algorithm. This paper evaluates the merits and trade-offs of the protocol design towards developing more efficient and practical algorithms for objectposition estimation.
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spelling doaj.art-ebea720a04de45c8bc9211d3901a661a2022-12-22T04:02:01ZengMDPI AGSensors1424-82202012-11-011211153081533710.3390/s121115308Decentralized Cooperative TOA/AOA Target Tracking for Hierarchical Wireless Sensor NetworksChih-Yu WenYing-Chih ChenThis paper proposes a distributed method for cooperative target tracking in hierarchical wireless sensor networks. The concept of leader-based information processingis conducted to achieve object positioning, considering a cluster-based network topology. Random timers and local information are applied to adaptively select a sub-cluster for thelocalization task. The proposed energy-efficient tracking algorithm allows each sub-clustermember to locally estimate the target position with a Bayesian filtering framework and a neural networking model, and further performs estimation fusion in the leader node with the covariance intersection algorithm. This paper evaluates the merits and trade-offs of the protocol design towards developing more efficient and practical algorithms for objectposition estimation.http://www.mdpi.com/1424-8220/12/11/15308wireless sensor networkstarget trackingBayesian filteringneural networkingcovariance intersection
spellingShingle Chih-Yu Wen
Ying-Chih Chen
Decentralized Cooperative TOA/AOA Target Tracking for Hierarchical Wireless Sensor Networks
Sensors
wireless sensor networks
target tracking
Bayesian filtering
neural networking
covariance intersection
title Decentralized Cooperative TOA/AOA Target Tracking for Hierarchical Wireless Sensor Networks
title_full Decentralized Cooperative TOA/AOA Target Tracking for Hierarchical Wireless Sensor Networks
title_fullStr Decentralized Cooperative TOA/AOA Target Tracking for Hierarchical Wireless Sensor Networks
title_full_unstemmed Decentralized Cooperative TOA/AOA Target Tracking for Hierarchical Wireless Sensor Networks
title_short Decentralized Cooperative TOA/AOA Target Tracking for Hierarchical Wireless Sensor Networks
title_sort decentralized cooperative toa aoa target tracking for hierarchical wireless sensor networks
topic wireless sensor networks
target tracking
Bayesian filtering
neural networking
covariance intersection
url http://www.mdpi.com/1424-8220/12/11/15308
work_keys_str_mv AT chihyuwen decentralizedcooperativetoaaoatargettrackingforhierarchicalwirelesssensornetworks
AT yingchihchen decentralizedcooperativetoaaoatargettrackingforhierarchicalwirelesssensornetworks