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

机译:基于Cycrationary的生命体征在2.5 GHz下使用微波雷达检测

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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:生命体征,如呼吸心跳频率的非接触检测,估计是用于监控应用的有力工具。特别地,连续波生物雷达已被广泛研究,以确定在一个非接触方式的生理参数。由于来自人体的RF反射信号由噪声和随机身体运动损坏,传统的傅立叶分析未能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呼吸频率和心脏率的非侵入式测量雷达的性能。然而,前期工作只集中在一个频率上,不包括衰减的身体在分析影响和随机运动。因此,在本文中,我们评估距离和噪声对反射信号的循环特征的影响。此外,我们通过发展循环平均,共轭循环自相关和循环累积探索的二阶循环平稳信号处理性能的评估。此外,分析是使用样本的数目减少,以减少响应时间。使用在2.5GHz的双基地雷达配置的循环平稳技术的实现被示出作为一个例子说明了该方法。

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