Ultra Low-Latency Backscatter for Fast-Moving Location Tracking
Jingxian Wang, Vaishnavi Nattar Ranganathan, Jonathan Lester, Swarun Kumar
摘要
This paper explores building an ultra-low latency and high-accuracy location tracking solution using battery-free tags. While there is rich prior work on location tracking with battery-free RFID tags and backscatter devices, these systems typically face tradeoffs with accuracy, power consumption, and latency. Such limitations make these existing solutions unsuitable for emerging applications like industrial augmented reality which requires tracking fast-moving machinery; monitoring indoor sports activities that require real-time tracking of fast-moving objects with high precision and under stringent latency constraints.
We propose and demonstrate FastLoc, a precision tracking system that locates tiny, battery-free analog backscatter tags at sub-millisecond latency and sub-centimeter accuracy. FastLoc is a hybrid system that simultaneously uses RF and optical signals to track tiny tags that can be attached to everyday objects. FastLoc leverages the RF channel responses from tags for estimating the coarse region where the tags may be located. It simultaneously uses the sensed optical information modulated on the backscatter signals to enable fine-grained location estimation within the coarse region. To achieve this, we design and fabricate a custom analog tag that consumes less than 150 𝑢𝑊 and instantaneously converts incident optical signals to one-shot wideband harmonic RF responses at nanosecond latency. We then develop a static high-density distributed-frequency structured light pattern that can localize tags in the area of interest at a sub-centimeter accuracy and microsecond-scale latency. A detailed experimental evaluation of FastLoc shows a median accuracy of 0.7 cm in tag localization with a 0.51 ms effective localization latency.
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- Millimetro: mmWave retro-reflective tags for accurate, long range localizationElahe Soltanaghaei, Akarsh Prabhakara, Artur Balanuta, Matthew G. Anderson 等MobiCom 2021 · 被引用 111 次
- RFID Tattoo: A Wireless Platform for Speech RecognitionJingxian Wang, Chengfeng Pan, Haojian Jin, Vaibhav Singh 等UbiComp 2020 · 被引用 57 次
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