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RoSense: Refining LOS Signal Phase for Robust RFID Sensing via Spinning Antenna
IEEE Internet of Things Journal ( IF 8.2 ) Pub Date : 7-25-2022 , DOI: 10.1109/jiot.2022.3191947
Yinan Zhu 1 , Chunhui Duan 2 , Xuan Ding 1 , Zheng Yang 1
Affiliation  

RFID sensing leveraging backscatter signal features (e.g., phase shift) from tags has gained increasing popularity in numerous applications but also suffers from negative impacts of environmental multipaths. Past works to address it rely on extra customized devices, labor-intensive offline training, or frequency channel hopping, all of which are non-ubiquitous or ineffective for real-life adoption. This article presents RoSense, a universal method to alleviate multipath reflections’ impacts by spinning the reader antenna, thus enabling more robust RFID sensing. Besides, RoSense requires no RF devices or offline training and operates in a nonintrusive manner. The key insight of RoSense is to exploit two properties of line-of-sight (LOS) signal when spinning the antenna, i.e., the linearity of phase changes and stability of received signal strength to attenuate the nonlinear and nonmonotonic effect of multipath signals and refine the phase shift of LOS signal. We have implemented a prototype of RoSense with COTS devices and studied two cases for evaluation: 1) material identification and 2) object localization. Experimental results show that RoSense can improve the material identification accuracy by up to 16.22% and reduce the mean localization error by up to 39.93%, greatly outperforming the state-of-the-art solutions.

中文翻译:


RoSense:通过旋转天线改进 LOS 信号相位以实现稳健的 RFID 传感



利用标签反向散射信号特征(例如相移)的RFID传感在众多应用中越来越受欢迎,但也受到环境多路径的负面影响。过去解决这个问题的工作依赖于额外的定制设备、劳动密集型离线培训或频道跳频,所有这些对于现实生活中的采用来说并不普遍或无效。本文介绍了 RoSense,这是一种通过旋转读取器天线来减轻多路径反射影响的通用方法,从而实现更强大的 RFID 传感。此外,RoSense 不需要射频设备或离线培训,并且以非侵入式方式运行。 RoSense 的关键见解是利用天线旋转时视距 (LOS) 信号的两个特性,即相位变化的线性度和接收信号强度的稳定性,来衰减多径信号的非线性和非单调效应,并细化LOS 信号的相移。我们使用 COTS 设备实现了 RoSense 原型,并研究了两种评估案例:1) 材料识别和 2) 对象定位。实验结果表明,RoSense 可以将材料识别精度提高高达 16.22%,将平均定位误差降低高达 39.93%,大大优于最先进的解决方案。
更新日期:2024-08-22
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