Paper
7 March 2022 Research on radar gesture recognition algorithm based on multidimensional parameter fusion
Yang Xu, Changrui Sui, Jingtao Zhang, Jianjie Yang
Author Affiliations +
Proceedings Volume 12167, Third International Conference on Electronics and Communication; Network and Computer Technology (ECNCT 2021); 1216730 (2022) https://doi.org/10.1117/12.2628768
Event: 2021 Third International Conference on Electronics and Communication, Network and Computer Technology, 2021, Harbin, China
Abstract
This paper proposes a gesture recognition method based on frequency modulated continuous wave radar. The radar echo signal reflected when the hand moves is analyzed and processed in the time and frequency domain to extract the multidimensional parameters such as Doppler, range, and horizontal angle of the gesture. These parameters are spliced into a Range-Doppler-Time-Map and Range-Horizontal-Angle-Time-Map according to a fixed frame length to form a data set containing six kinds of gestures. Finally, a shallow convolutional neural network with only 5 layers is used to recognize and classify six gestures. The experimental results show that, compared with the traditional single parameter features such as Range-Time features and Doppler-Time features, the combined features of Range-Doppler-Time and Range-HorizontalTime can more accurately deal with the six gestures.
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Yang Xu, Changrui Sui, Jingtao Zhang, and Jianjie Yang "Research on radar gesture recognition algorithm based on multidimensional parameter fusion", Proc. SPIE 12167, Third International Conference on Electronics and Communication; Network and Computer Technology (ECNCT 2021), 1216730 (7 March 2022); https://doi.org/10.1117/12.2628768
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KEYWORDS
Radar

Gesture recognition

Doppler effect

Convolutional neural networks

Radar signal processing

Image classification

Detection and tracking algorithms

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