TRTAR: Transmissive RIS-assisted Through-the-wall Human Activity Recognition

TL;DR

TRTAR eliminates the necessity for dedicated devices or noise removal algorithms, while specifically addressing signal propagation through walls, while specifically addressing signal propagation through walls.

Abstract

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% when signals traverse concrete walls.

Figures (6)

• Figure 1: Photography of the 1-bit transmissive RIS prototype (left side), and the logic circuit controlling board (right side).
• Figure 2: Floor plans of the experimental environment with concrete wall.
• Figure 3: The spectrum of the transmissive RIS test: (a) without RIS, (b) with RIS.
• Figure 4: Overall architecture of the proposed HAR system.
• Figure 5: The variation of the amplitude of CSI data when a person is performing specific activities.