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Gesture Classification with Handcrafted Micro-Doppler Features using a FMCW Radar

: Sun, Y.; Fei, T.; Schliep, F.; Pohl, N.


IEEE Microwave Theory and Techniques Society:
IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM) 2018 : 16-18 April 2018, Munich, Germany
Piscataway, NJ: IEEE, 2018
ISBN: 978-1-5386-1725-0
ISBN: 978-1-5386-1724-3
ISBN: 978-1-5386-1726-7
4 pp.
International Conference on Microwaves for Intelligent Mobility (ICMIM) <4, 2018, Munich>
Conference Paper
Fraunhofer FHR ()

This paper deals with gesture recognition using a 77 GHz FMCW radar system based on the micro-Doppler (μ D) signatures. In addition to the Doppler information, the range information is also available in the FMCW radar. Therefore, it is utilized to filter out the irrelevant targets. We have proposed five micro-Doppler based handcrafted features for gesture recognition. Finally, a simple k-nearest neighbor (k-NN) classifier is applied to evaluate the importance of the five features. The classification results demonstrate that the proposed features can guarantee a promising recognition accuracy.