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RFID Multi-Target Tracking Using the Probability Hypothesis Density Algorithm for a Health Care Application
Responsible organisation
2011 (English)Conference paper, (Refereed) 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.

Place, publisher, year, edition, pages
Córdoba, Spain: Springer , 2011.
Keyword [en]
Human Tracking, Probability Hypothesis Density, Radio Frequency Identification.
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:bth-7460Local ID: oai:bth.se:forskinfo4B93A9E60F19D417C12578FF0047E5CBOAI: oai:DiVA.org:bth-7460DiVA: diva2:835081
Conference
3rd International ICST Conference on IT Revolutions
Available from: 2012-09-18 Created: 2011-09-02 Last updated: 2015-06-30Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NO
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  • Other locale
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Output format
  • html
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