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Representing arbitrary sensor observations for target tracking in wireless sensor networks

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dc.contributor.authorSleep, S.R.
dc.contributor.authorDadej, A.
dc.contributor.authorLee, I.
dc.date.issued2017
dc.description.abstractConventional object tracking in wireless sensor networks requires the use of predefined sensor types, which presents challenges when faced with adaptability and scalability constraints. This paper considers heterogeneous sensors and proposes a sensor-independent tracking framework. The Adaptive Grid Representation of belief Distribution (Adaptive GRiD) provides a common data format to allow heterogeneous sensors to be treated homogeneously. The proposed framework has been evaluated by simulation, and the results demonstrate that the Adaptive GRiD technique yields improved location estimation over a conventional occupancy grid approach.
dc.identifier.citationComputers and Electrical Engineering, 2017; 64:354-364
dc.identifier.doi10.1016/j.compeleceng.2016.11.033
dc.identifier.issn0045-7906
dc.identifier.issn1879-0755
dc.identifier.orcidLee, I. [0000-0002-2826-6367]
dc.identifier.urihttps://hdl.handle.net/11541.2/124243
dc.language.isoen
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD
dc.rightsCopyright 2016 Elsevier Access Condition Notes: Accepted manuscript available after 1 January 2019
dc.source.urihttps://doi.org/10.1016/j.compeleceng.2016.11.033
dc.subjectwireless sensor network
dc.subjecttarget tracking
dc.subjectheterogeneous sensors
dc.subjectadaptive state space
dc.subjectnonparametric representation
dc.subjectoccupancy grid
dc.titleRepresenting arbitrary sensor observations for target tracking in wireless sensor networks
dc.typeJournal article
pubs.publication-statusPublished
ror.mmsid9916109490201831

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