智能环境下的智能设备:真实环境下的无设备被动检测

May Moussa, M. Youssef
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引用次数: 193

摘要

无设备被动定位(DfP)是一种用于检测、跟踪和识别不携带任何设备、也不积极参与定位过程的实体的系统。DfP系统允许使用名义上的WiFi设备进行入侵检测,而无需使用任何额外的硬件,为任何支持WiFi的设备增加了智能。本文重点研究了DfP系统在实际环境中的检测功能。我们表明,我们之前开发的检测算法在受控环境中的性能达到了100%的召回率和精确度,但在真实环境中进行测试时,性能明显下降。我们提出了一种基于极大似然估计(MLE)的替代算法,该算法在真实环境中具有显著的性能提高。结果表明,在不影响系统精度的情况下,系统的召回率提高了10%以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart cevices for smart environments: Device-free passive detection in real environments
Device-free Passive (DfP) localization is a system envisioned to detect, track, and identify entities that do not carry any device, nor participate actively in the localization process. A DfP system allows using nominal WiFi equipment for intrusion detection, without using any extra hardware, adding smartness to any WiFi-enabled device. In this paper, we focus on the detection function of the DfP system in a real environment. We show that the performance of our previously developed algorithms for detection in a controlled environments, which achieved 100% recall and precision, degrades significantly when tested in a real environment. We present an alternative algorithm, based on the maximum likelihood estimator (MLE), that has a significant performance increase in a real environment. Our results show that the recall of the system increases by more than 10% when using the proposed MLE without affecting the system's precision.
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