CNN-Based Driver Monitoring Using Millimeter-Wave Radar Sensor

In this letter, we propose a method of monitoring driver's movement using a small-sized millimeter-wave radar sensor. First, we install a frequency-modulated continuous wave radar sensor on the steering wheel and collect reflected signals for various driver motions. Because the reflection patte...

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Bibliographic Details
Published in:IEEE sensors letters 2021-03, Vol.5 (3), p.1-4
Main Authors: Jung, Jaehoon, Lim, Sohee, Kim, Byung-Kwan, Lee, Seongwook
Format: Article
Language:English
Subjects:
Artificial neural networks
Computer architecture
Continuous wave radar
driver monitoring
Head
Image classification
Microwave/millimeter wave sensors
Military communications
Millimeter waves
millimeter-wave (mmWave) radar
Monitoring
pattern classification
Radar
Radar imaging
Sensors
Signal classification
Spectrogram
Training
Vehicles
Window functions
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Description
Summary:In this letter, we propose a method of monitoring driver's movement using a small-sized millimeter-wave radar sensor. First, we install a frequency-modulated continuous wave radar sensor on the steering wheel and collect reflected signals for various driver motions. Because the reflection patterns are different for each motion, we can distinguish different movements of the driver by analyzing the received signal. In our method, we use the spectrogram of the received signal obtained through multiple measurements and apply a window function to extract the radar signal in the form of an image. Then, we use the convolutional neural network architecture to classify the radar signal images. The classification results show that our proposed method can classify four different movements of the driver with an accuracy higher than 80%.
ISSN:2475-1472
2475-1472
DOI:10.1109/LSENS.2021.3063086