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arXiv · 1908.04417

Low-cost low-power in-vehicle occupant detection with mm-wave FMCW radar

Mostafa Alizadeh·Hajar Abedi·George Shaker
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Abstract

In this paper, we use a low-cost low-power mm-wave frequency modulated continuous wave (FMCW) radar for the in-vehicle occupant detection. We propose an algorithm using Capon filter for the joint range-azimuth estimation. Then, the minimum necessary features are extracted to train machine learning classifiers to have reasonable computational complexity while achieving high accuracy. In addition, experiments were carried out in a minivan to detect occupancy of each row using support vector machine (SVM). Finally, our proposed system achieved 97.8% accuracy on average in finding the defined scenarios. Moreover, the system can correctly identify if the vehicle is occupied or not with 100% accuracy.

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Mostafa Alizadeh, Hajar Abedi, George Shaker. 2019-08-12. Low-cost low-power in-vehicle occupant detection with mm-wave FMCW radar. https://doi.org/10.1109/sensors43011.2019.8956880

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