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PADS: Passive detection of moving targets with dynamic speed using PHY layer information

机译:PADS:使用PHY层信息以动态速度被动检测运动目标

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Device-free passive detection is an emerging technology to detect whether there exists any moving entities in the area of interests without attaching any device to them. It is an essential primitive for a broad range of applications including intrusion detection for safety precautions, patient monitoring in hospitals, child and elder care at home, etc. Despite of the prevalent signal feature Received Signal Strength (RSS), most robust and reliable solutions resort to finer-grained channel descriptor at physical layer, e.g., the Channel State Information (CSI) in the 802.11n standard. Among a large body of emerging techniques, however, few of them have explored full potentials of CSI for human detection. Moreover, space diversity supported by nowadays popular multi-antenna systems are not investigated to the comparable extent as frequency diversity. In this paper, we propose a novel scheme for device-free PAssive Detection of moving humans with dynamic Speed (PADS). Both amplitude and phase information of CSI are extracted and shaped into sensitive metrics for target detection; and CSI across multi-antennas in MIMO systems are further exploited to improve the detection accuracy and robustness. We prototype PADS on commercial WiFi devices and experiment results in different scenarios demonstrate that PADS achieves great performance improvement in spite of dynamic human movements.
机译:无设备被动检测是一种新兴技术,用于检测目标区域中是否存在任何移动实体而无需将任何设备连接到它们。它是广泛应用的基本原语,包括用于安全预防措施的入侵检测,医院中的患者监视,家庭中的儿童和老人护理等。尽管具有普遍的信号功能接收信号强度(RSS),但最健壮和可靠的解决方案在物理层上求助于更细粒度的信道描述符,例如802.11n标准中的信道状态信息(CSI)。但是,在一大堆新兴技术中,很少有人探索出CSI用于人类检测的全部潜力。此外,当今流行的多天线系统所支持的空间分集还没有像频率分集那样得到研究。在本文中,我们提出了一种新的方案,用于以动态速度(PADS)对移动人员进行无设备被动检测。 CSI的幅度和相位信息均被提取并整形为用于目标检测的敏感指标;进一步利用MIMO系统中跨多天线的CSI和CSI来提高检测精度和鲁棒性。我们在商用WiFi设备上对PADS进行了原型设计,并且在不同场景下的实验结果表明,尽管动态人体运动,PADS仍可以实现很大的性能提升。

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