基于阵列雷达和呼吸空间聚类的任意位置多人非接触呼吸测量
Noncontact Respiratory Measurement for Multiple People at Arbitrary Locations Using Array Radar and Respiratory-Space Clustering
摘要：
我们开发了一个非接触式测量系统，用于监测多个人的呼吸使用毫米波阵列雷达。为了分离多个人的雷达回波，常规技术在时域、频域或空域中对雷达回波进行聚类。针对多人呼吸信号的测量问题，提出了一种基于空间聚类的方法，有效利用呼吸频率的个体差异，准确分辨人体回波。所提出的空间聚类可以分离回声，即使当人们位于彼此接近。此外，该方法可以应用于目标的数量是未知的，可以准确地估计的人数和位置。我们进行了多个实验，涉及五个或七个参与者，以验证所提出的方法的性能，并定量评估的人数和呼吸间隔的估计精度。实验结果表明，该方法估计呼吸间隔的平均均方根误差为196 ms。使用所提出的方法，而不是传统的方法，提高了85.0%的人的数量的估计的准确性，这表明所提出的方法的有效性的测量的多个人的呼吸。
英文摘要：
We developed a noncontact measurement system for monitoring the respiration of multiple people using millimeter-wave array radar. To separate the radar echoes of multiple people, conventional techniques cluster the radar echoes in the time, frequency, or spatial domain. Focusing on the measurement of the respiratory signals of multiple people, we propose a method called respiratory-space clustering, in which individual differences in the respiratory rate are effectively exploited to accurately resolve the echoes from human bodies. The proposed respiratory-space clustering can separate echoes, even when people are located close to each other. In addition, the proposed method can be applied when the number of targets is unknown and can accurately estimate the number and positions of people. We perform multiple experiments involving five or seven participants to verify the performance of the proposed method, and quantitatively evaluate the estimation accuracy for the number of people and the respiratory intervals. The experimental results show that the average root-mean-square error in estimating the respiratory interval is 196 ms using the proposed method. The use of the proposed method, rather the conventional method, improves the accuracy of the estimation of the number of people by 85.0%, which indicates the effectiveness of the proposed method for the measurement of the respiration of multiple people.
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