Song Heemang, Shin Hyun-Chool
Department of Software Convergence, Soongsil University, Seoul 06978, Korea.
Entropy (Basel). 2021 Nov 8;23(11):1472. doi: 10.3390/e23111472.
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.
在本文中,我们给出了使用单通道调频连续波雷达获得的车内多乘客占用检测结果。在时频域中分析雷达信号的生理特征,并基于这些特征提出用于多乘客占用检测的特征。在应用杂波去除后,提出频谱功率和维纳熵作为量化由呼吸和心跳引起的生理运动的特征。利用座位1和座位2处功率和维纳熵的平均值来表示特征分布,并进行分类。使用线性判别分析和最大似然估计来评估多乘客占用检测性能。结果表明,所提出的功率和维纳熵是用于多乘客占用检测的有效特征。