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Human motion classification using a particle filter approach: multiple model particle filtering applied to the micro-Doppler spectrum

Published online by Cambridge University Press:  23 April 2013

Stephan Groot
Affiliation:
Delft University of Technology, Microwave Sensing – Systems and Signals, Delft, The Netherlands
Ronny Harmanny*
Affiliation:
Thales Nederland B.V., Surface Radar, Delft/Hengelo, The Netherlands. Phone: +31 15 251 78 29.
Hans Driessen
Affiliation:
Thales Nederland B.V., Surface Radar, Delft/Hengelo, The Netherlands. Phone: +31 15 251 78 29.
Alexander Yarovoy
Affiliation:
Delft University of Technology, Microwave Sensing – Systems and Signals, Delft, The Netherlands
*
Corresponding author: R. Harmanny Email: ronny.harmanny@nl.thalesgroup.com

Abstract

In this article, a novel motion model-based particle filter implementation is proposed to classify human motion and to estimate key state variables, such as motion type, i.e. running or walking, and the subject's height. Micro-Doppler spectrum is used as the observable information. The system and measurement models of human movements are built using three parameters (relative torso velocity, height of the body, and gait phase). The algorithm developed has been verified on simulated and experimental data.

Type
Research Papers
Copyright
Copyright © Cambridge University Press and the European Microwave Association 2013 

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References

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