摘要翻译：
非接触式生命体征检测在病人监护和静态人体检测等许多领域都有广泛的应用。在过去的十年里，雷达作为一种智能和方便的传感器被引入到非接触式呼吸监测中。雷达传感器因其能够穿越障碍物和在恶劣的环境条件下工作而被认为适合于这种应用。FMCW雷达以其既能探测呼吸目标的位置，又能探测因呼吸而引起的胸部微动而成为该领域的有力工具。现有的用于呼吸检测的雷达技术大多是基于对距离或多普勒维所需谐波的带通滤波或小波变换。然而，这两种技术都影响了监测的实时性，并且在有限的距离和角度下工作。由于呼吸、胸部运动，在接收到的距离谱中观察到一个可识别的波动效应。本文提出的技术是基于实时检测和处理功率在不同角度和距离上的变化。对工作在不同载波频段、带宽和输出功率电平下的两种雷达模块进行了测试和比较。
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英文标题：
《Power-Based Real-Time Respiration Monitoring Using FMCW Radar》
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作者：
Sherif Abdulatif, Fady Aziz, Pelin Altiner, Bernhard Kleiner, Urs
  Schneider
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最新提交年份：
2017
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分类信息：

一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Signal Processing        信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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英文摘要：
  Non-contact vital sign detection is a required application nowadays in many fields as patient monitoring and static human detection. Within the last decade, radar has been introduced as a smart and convenient sensor for non-contact respiration monitoring. Radar sensors are considered suitable for such application for its capability to work through obstacles and in harsh environmental conditions. FMCW radar has been introduced as a powerful tool in this field for its capability of detecting both the breathing target position and his chest micro-motions induced due to breathing. Most of the presented techniques for using the radar for respiration detection is based on bandpass filtering or wavelet transforms on the required harmonics in either the range or Doppler dimension. However, both techniques affect the real-time capability of the monitoring and work on limited distances and aspect angles. A recognizable fluctuation effect is observed in the received range spectrum overtime due to respiration chest movements. The proposed technique in this paper is based on detecting and processing the power changes in real-time over different aspect angles and distances. Two radar modules working on different carrier frequency bands, bandwidths and output power levels were tested and compared.
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PDF链接：
https://arxiv.org/pdf/1711.09198