Static person detection and localization with estimation of person's breathing rate using single multistatic UWB radar

D. Novak, D. Kocur, J. Demcak
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引用次数: 2

Abstract

In the past period, great efforts have been made to develop the methods for the detection of human beings based on a monitoring their respiratory motion. For that purpose, ultra-wideband sensors (radars) operating in the frequency band DC-5GHz can be used with advantage. The basic principle of respiratory motion detection consists in the identification of sensor signal components possessing a significant power in the frequency band 0.2–0.7 Hz (frequency band of a human respiratory rate) corresponding to a constant range between the target and radar. However, the problem of person localization associated with the estimation of their breathing rate has not been studied deeply. In order to fill this gap, an approach for a joint localization and breathing rate estimation of a person will be introduced in this chapter. For that purpose, a combination of a method for the static person localization based on power-spectrum estimation using Welch periodogram referred to as WP-STAPELOC method and the Welch periodogram, MUSIC algorithm and Burg methods for the estimation of a fundamental harmonic of respiratory motion will be introduced. The performance of proposed procedure will be evaluated using a data obtained at experimental scenario. Moreover, a reference measurement will be performed in order to compare the results from UWB radar with the results from the optical sensor.
基于单台多静态超宽带雷达呼吸频率估计的静态人检测与定位
在过去的一段时间里,人们一直在努力开发基于监测呼吸运动的人体检测方法。为此,可以使用在DC-5GHz频段工作的超宽带传感器(雷达)。呼吸运动检测的基本原理在于识别目标与雷达之间一定距离内对应的0.2-0.7 Hz频带(人体呼吸频率频带)内具有显著功率的传感器信号分量。然而,与呼吸频率估计相关的人定位问题尚未得到深入研究。为了填补这一空白,本章将介绍一种用于人体关节定位和呼吸频率估计的方法。为此,本文将介绍一种基于Welch周期图的功率谱估计的静态人定位方法(称为WP-STAPELOC方法)与Welch周期图、MUSIC算法和Burg方法的组合,用于估计呼吸运动的基本谐波。所提出的程序的性能将使用在实验场景中获得的数据进行评估。此外,将进行参考测量,以便将超宽带雷达的结果与光学传感器的结果进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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