【论文阅读整理】TagFi: Locating Ultra-Low Power WiFi Tags Using Unmodified WiFi Infrastructure
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【论文阅读整理】TagFi: Locating Ultra-Low Power WiFi Tags Using Unmodified WiFi Infrastructure
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原文鏈接:
https://www.researchgate.net/publication/350505530_TagFi_Locating_Ultra_Low_Power_WiFi_Tags_Using_Unmodified_WiFi_Infrastructure
這是卡內基梅隆大學 ELAHE SOLTANAGHAEI 于2021年3月份發表的一篇利用WiFi實現有源定位的文章,利用WiFi信號的 CSI 獲得 AoA、DoA 和 ToF,對目標位置進行估計,定位精度為0.2m。
Contributions:
- TagFi: a novel tag localization and identification system that only uses the existing WiFi infrastructure and commodity wireless devices. So, it fully piggybacks tag localization on regular WiFi communications without requiring devices to operate in different frequency channels.
- Asynchronous tag design: We use a tag design that is fully asynchronous in favor of practicality, which enables a minimal architecture at the tag while addressing the high in-band interference with more powerful signal processing techniques at the receiver.
- Code-optimized super resolution: TagFi leverages the backscatter modulation and spatial structure of the signal to overcome complex multipath interference. This enables extracting a weak wireless reflection in the presence of strong line-of-sight path. While this method is general, we show that it enables tag localization with no need for complex operations at the tag such as frequency shifting.
- Single-point localization: TagFi provides decimeter-level tag localization from a single channel in a single WiFi receiver. So, combined with asynchronous tag architecture and its compatibility with existing WiFi infrastructure, it enables a new primitive of ubiquitous and infrastructure-less sensing and localization.
System design
Localization algorithm
where Tx(xt,yt)T_x(x_t,y_t)Tx?(xt?,yt?), Rx(0,0)R_x(0,0)Rx?(0,0), Tag(x,y)Tag(x,y)Tag(x,y), a=(xt2+yt2)1/2a = (x_t^2+y_t^2)^{1/2}a=(xt2?+yt2?)1/2
where QQQ is the number of WiFi transmitters.
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