用菲涅尔区模型探究WiFi感知系统的稳定性

Exploring Stability in WiFi Sensing System Based on Fresnel Zone Model

基于WiFi的非接触感知系统利用环境中广泛存在的WiFi信号在自然情况下对用户活动进行感知,具有十分广阔的应用前景。从细粒度活动到粗粒度活动,现有工作进行了大量的探索,但尚未理解和解决感知系统稳定性不足的问题。当感知对象、收发设备位置、测试环境等发生变化时,系统性能会受到严重影响。实际上,人体活动对应的接收信号模式因位置和朝向的变化而带来的不一致性导致了系统不能稳定工作。为了理解这种现象的本质,利用团队提出的基于无线感知的菲涅尔区衍射和反射模型,精确定量刻画了目标物体相对于收发设备的位置、运动轨迹和无线信号波形模式之间的关系。通过两个应用实例,即细粒度的手指动作识别和粗粒度的健身活动识别,在模型的指导下,分别解释了系统不能稳定工作的原因,说明了如何得到一致的感知波形,以及如何构造可区分的感知波形,并给出了提升感知系统性能的方法。

WiFi based contactless sensing systems use pervasive wireless communication signals in the environment to sense human activities in a natural way,enabling many promising applications.From fine-grained activity sensing to coarse-grained activity recognition,existing work have done a great deal of exploration.However,there is lack of understanding and tackling the serious unstable sensing performance problem.While changing the human target,the position of transceivers,and test environment,the system performance is severely degraded.The reason behind the instability of WiFi-based sensing system is that human activities induce the inconsistent signal patterns inherently at different positions.This paper proposes the Fresnel zone-based diffraction and reflection sensing model,which can be used to accurately quantify the relationship between the target􀆳s position with respect to the transceiver,movement trajectory and the signal variation pattern.By illustrating two application examples,i.e.,fine-grained finger gesture recognition and coarse-grained fitness activity recognition,and guided by the sensing model,this paper explores the reason behind the unstable performance for sensing system.This paper clearly explains how to obtain the consistent signal patterns and how to generate easily distinguishable signal patterns,further presents the methods to improve the performance of wireless sensing systems.