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RFID Multi-Target Tracking Using the Probability Hypothesis Density Algorithm for a Health Care Application
Ansvarig organisation
2011 (Engelska)Konferensbidrag, Publicerat paper (Refereegranskat) Published
Abstract [en]

The intelligent multi-sensor system is a system for target detection, identification and information processing for human activities surveillance and ambient assisted living. This paper describes RFID multi-target tracking using the Gaussian Mixture Probability Hypothesis Density, GM-PHD, algorithm. The multi target tracking ability of the proposed solution is demonstrated in a simulation and real environment. A performance comparison of the Levenberg-Marquardt algorithm with and without the GM-PHD filter shows that the GM-PHD algorithm improves the accuracy of tracking and target position estimation significantly. This improvement is demonstrated by a simulation and by a physical experiment.

Ort, förlag, år, upplaga, sidor
Córdoba, Spain: Springer , 2011.
Nyckelord [en]
Human Tracking, Probability Hypothesis Density, Radio Frequency Identification.
Nationell ämneskategori
Signalbehandling
Identifikatorer
URN: urn:nbn:se:bth-7460Lokalt ID: oai:bth.se:forskinfo4B93A9E60F19D417C12578FF0047E5CBOAI: oai:DiVA.org:bth-7460DiVA, id: diva2:835081
Konferens
3rd International ICST Conference on IT Revolutions
Tillgänglig från: 2012-09-18 Skapad: 2011-09-02 Senast uppdaterad: 2015-06-30Bibliografiskt granskad

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Kulesza, Wlodek

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