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Cyclostationary-Based Vital Signs Detection Using Microwave Radar at 2.5 GHz

机译:使用2.5 GHz微波雷达的基于循环平稳的生命体征检测

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摘要

Non-contact detection and estimation of vital signs such as respiratory and cardiac frequencies is a powerful tool for surveillance applications. In particular, the continuous wave bio-radar has been widely investigated to determine the physiological parameters in a non-contact manner. Since the RF-reflected signal from the human body is corrupted by noise and random body movements, traditional Fourier analysis fails to detect the heart and breathing frequencies. In this effort, cyclostationary analysis has been used to improve the radar performance for non-invasive measurement of respiratory rate and heart rate. However, the preliminary works focus only on one frequency and do not include the impact of attenuation and random movement of the body in the analysis. Hence in this paper, we evaluate the impact of distance and noise on the cyclic features of the reflected signal. Furthermore, we explore the assessment of second order cyclostationary signal processing performance by developing the cyclic mean, the conjugate cyclic autocorrelation and the cyclic cumulant. In addition, the analysis is carried out using a reduced number of samples to reduce the response time. Implementation of the cyclostationary technique using a bi-static radar configuration at 2.5 GHz is shown as an example to demonstrate the proposed approach.
机译:非接触式检测和估计生命体征(如呼吸频率和心脏频率)是监视应用程序的强大工具。特别地,连续波生物雷达已经被广泛研究以非接触方式确定生理参数。由于来自人体的射频反射信号会被噪声和随机运动所破坏,因此传统的傅立叶分析无法检测到心脏和呼吸频率。在这一努力中,循环平稳分析已被用于改善雷达性能,用于无创测量呼吸频率和心率。但是,初步工作仅集中在一个频率上,并未在分析中包括衰减和人体随机运动的影响。因此,在本文中,我们评估了距离和噪声对反射信号的周期性特征的影响。此外,我们通过开发循环均值,共轭循环自相关和循环累积量来探索对二阶循环平稳信号处理性能的评估。另外,使用减少数量的样品进行分析以减少响应时间。以使用双静态雷达配置在2.5 GHz频率下实现循环平稳技术为例,以演示所提出的方法。

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