Abstract
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.
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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Chen, J., Olayanju, I.D., Ojelabi, O.P., Kulesza, W. (2012). RFID Multi-target Tracking Using the Probability Hypothesis Density Algorithm for a Health Care Application. In: Liñán Reyes, M., Flores Arias, J.M., González de la Rosa, J.J., Langer, J., Bellido Outeiriño, F.J., Moreno-Munñoz, A. (eds) IT Revolutions. IT Revolutions 2011. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 82. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32304-1_9
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DOI: https://doi.org/10.1007/978-3-642-32304-1_9
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