Abstract
In this paper, we provide the results of multi-passenger occupancy detection inside a vehicle obtained using a single-channel frequency-modulated continuous-wave radar. The physiological characteristics of the radar signal are analyzed in a time-frequency spectrum, and features are proposed based on these characteristics for multi-passenger occupancy detection. After clutter removal is applied, the spectral power and Wiener entropy are proposed as features to quantify physiological movements arising from breathing and heartbeat. Using the average means of both the power and Wiener entropy at seats 1 and 2, the feature distributions are expressed, and classification is performed. The multi-passenger occupancy detection performance is evaluated using linear discriminant analysis and maximum likelihood estimation. The results indicate that the proposed power and Wiener entropy are effective features for multi-passenger occupancy detection.
Highlights
IntroductionThe development of autonomous vehicles has resulted in increasing interest in automobile safety technologies
Single-Channel frequency-modulated continuouswave (FMCW)-Radar-BasedThe development of autonomous vehicles has resulted in increasing interest in automobile safety technologies
To quantify a person’s physiological characteristics, we examined various features such as the spectral power and Wiener entropy [19], which quantify the flatness of the power spectral density (PSD)
Summary
The development of autonomous vehicles has resulted in increasing interest in automobile safety technologies. Typical applications of automobile safety technologies are present in passenger safety systems, such as passenger-side airbags and seat belt reminders. In this technology, whether a passenger is occupying a seat must be determined [1]. The prevention of children dying of heat stroke inside a vehicle will be discussed [2,3]. The United States is mandating the use of a rear occupant alert system in cars [5]. It is clear that passenger occupancy detection in vehicles has become increasingly important
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