Radar gesture recognition based on lightweight convolutional neural network

Yaoyao Dong; Wei Qu; Pengda Wang; Haohao Jiang; Tianhao Gao; Yanhe Shu

doi:10.1117/12.2607671

15 February 2022 Radar gesture recognition based on lightweight convolutional neural network

Yaoyao Dong, Wei Qu, Pengda Wang, Haohao Jiang, Tianhao Gao, Yanhe Shu

Proceedings Volume 12166, Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021); 121660W (2022) https://doi.org/10.1117/12.2607671
Event: Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021), 2021, Hong Kong, Hong Kong

Abstract

In order to effectively overcome the limitations of traditional gesture recognition technology, a method of gesture recognition using millimeter wave radar is proposed. First, according to the introduction of the millimeter-wave radar system and the description of the echo model, the millimeter-wave radar is used to collect the measured data; then the average cancellation method is used to suppress the clutter of the measured data, and the joint time-frequency analysis technology is used for effective feature extraction; The extracted features are used as the model input, and a lightweight convolutional neural network model is improved. Its recognition rate is over 96%, and it has good recognition performance.

Citation Download Citation

Yaoyao Dong, Wei Qu, Pengda Wang, Haohao Jiang, Tianhao Gao, and Yanhe Shu "Radar gesture recognition based on lightweight convolutional neural network", Proc. SPIE 12166, Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing (APCOM and YSAOM 2021), 121660W (15 February 2022); https://doi.org/10.1117/12.2607671

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KEYWORDS

Radar

Gesture recognition

Feature extraction

Convolutional neural networks

Sensors

Fourier transforms

Data modeling

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