- Title
- Dynamic clusters graph for detecting moving targets using WSNs
- Creator
- Armaghani, Farzaneh; Gondal, Iqbal; Kamruzzaman, Joarder; Green, David
- Date
- 2012
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/156709
- Identifier
- vital:11449
- Identifier
-
https://doi.org/10.1109/VTCFall.2012.6399265
- Identifier
- ISBN:1550-2252978-146731881-5
- Abstract
- Efficient target tracking applications require active sensor nodes to track a cluster of moving targets. Clustering could lead to significant cost improvement as compared to tracking individual targets. This paper presents accurate clustering of targets for both coherent and incoherent movement patterns. We propose a novel clustering algorithm that utilises an implicit dynamic time frame to assess the relational history of targets in creating a weighted graph of connected components. The proposed algorithm employs key features of localisation algorithms in target tracking, namely, estimated current and predicted locations to determine the relational directions and distances of moving targets. Our simulation results show a significant improvement on the clustering accuracy and computation time by dynamically adjusting the history-window size and predicting the relationships among targets.
- Publisher
- IEEE
- Relation
- 76th IEEE Vehicular Technology Conference, VTC Fall 2012; Quebec City, Canada; 3rd-6th September 2012 p. 1-5
- Rights
- Copyright © 2012 IEEE.
- Rights
- This metadata is freely available under a CCO license
- Subject
- Clustering algorithms; Target tracking; Weighted graph; Wireless sensor networks (WSNs)
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