TRTAR: Transmissive RIS-assisted Through-the-wall Human Activity Recognition
CoRR(2024)
摘要
Device-free human activity recognition plays a pivotal role in wireless
sensing. However, current systems often fail to accommodate signal transmission
through walls or necessitate dedicated noise removal algorithms. To overcome
these limitations, we introduce TRTAR: a device-free passive human activity
recognition system integrated with a transmissive reconfigurable intelligent
surface (RIS). TRTAR eliminates the necessity for dedicated devices or noise
removal algorithms, while specifically addressing signal propagation through
walls. Unlike existing approaches, TRTAR solely employs a transmissive RIS at
the transmitter or receiver without modifying the inherent hardware structure.
Experimental results demonstrate that TRTAR attains an average accuracy of
98.13
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