Energy efficient target tracking with particle filtering technique in wireless sensor networks

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dc.contributor.authorAlaybeyoglu A.
dc.date.accessioned2024-07-22T08:20:24Z
dc.date.available2024-07-22T08:20:24Z
dc.date.issued2011
dc.description.abstractIn this study, a new target tracking algorithm is proposed for wireless sensor networks. The aim of the algorithm is to decrease energy consumption of the system by decreasing the ratio of target misses. Next location of the target is predicted by using Particle Filtering (PF) technique which aims to represent the posterior density function by a set of random samples with associated weights. Nodes are deployed according to the hexagon shaped network topology in which each of the hexagons represents a cluster with a predetermined leader node. In order to decrease the ratio of target misses, nodes that are closer to the target's predicted location are woken up to make them ready to detect the target. This increases the probability of detecting the target by one of the neighboring hexagons when the target makes sudden turns or unexpected movements. Tracking performance of the proposed algorithm is evaluated by comparing with KNearest Cluster Tracking (KNCT), Wakening Based Target Tracking Algorithm (WBTA)[10] and Generic Static Tracking Approach (GSTA) in terms of miss ratio and energy consumption metrics. © Association for Scientific Research.
dc.identifier.issn1300686X
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/18142
dc.language.isoEnglish
dc.subjectClustering algorithms
dc.subjectElectric network topology
dc.subjectEnergy utilization
dc.subjectNonlinear filtering
dc.subjectSensors
dc.subjectTracking (position)
dc.subjectWireless sensor networks
dc.subjectClustering algorithms
dc.subjectClutter (information theory)
dc.subjectEnergy efficiency
dc.subjectEnergy utilization
dc.subjectMonte Carlo methods
dc.subjectSensor nodes
dc.subjectSignal filtering and prediction
dc.subjectTracking (position)
dc.subjectWireless sensor networks
dc.subjectDensity functions
dc.subjectEnergy consumption
dc.subjectEnergy efficient
dc.subjectNetwork topology
dc.subjectParticle Filtering
dc.subjectRandom sample
dc.subjectStatic tracking
dc.subjectTarget tracking algorithm
dc.subjectTracking performance
dc.subjectEnergy efficient
dc.subjectNetwork topology
dc.subjectParticle Filtering
dc.subjectRandom sample
dc.subjectStatic tracking
dc.subjectTarget tracking algorithm
dc.subjectTracking performance
dc.subjectTarget tracking
dc.subjectTarget tracking
dc.titleEnergy efficient target tracking with particle filtering technique in wireless sensor networks
dc.typeArticle

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