On the Use of Low-Cost Radars and Machine Learning for In-Vehicle Passenger Detection

Abstract

In this paper, we use a low-cost low-power mm-wave frequency
modulated continuous wave (FMCW) radar for in-vehicle occupant
monitoring. We propose an algorithm to identify occupied seats. In-
stead of using a high-resolution radar which increases the cost and
area, we integrate machine learning algorithms with the results of
covariance-based angle of arrival estimation capon beamformer.