Affiliation:
1. Northwest University, Xi'an, China
Abstract
Material sensing is crucial in many emerging applications, such as waste classification and hazardous material detection. Although existing Radio Frequency (RF) signal based systems achieved great success, they have limited identification accuracy when either RF signals can not penetrate through a target or a target has different outer and inner materials.
This paper introduces a Frequency Selective Surface (FSS) tag based high accuracy material identification system, namely FSS-Tag, which utilises both the penetrating signals and the coupling effect. Specifically, we design and attach a FSS tag to a target, and use frequency responses of the tag for material sensing, since different target materials have different frequency responses. The key advantage of our system is that, when RF signals pass through a target with the FSS tag, the penetrating signal responds more to the inner material, and the coupling effect (between the target and the tag) reflects more about the outer material; thus, one can achieve a higher sensing accuracy. The challenge lies in how to find optimal tag design parameters so that the frequency response of different target materials can be clearly distinguished. We address this challenge by establishing a tag parameter optimization model.
Real-world experiments show that FSS-Tag achieves more than 91% accuracy on identifying eight common materials, and improves the accuracy by up to 38% and 8% compared with the state of the art (SOTA) penetrating signal based method TagScan and the SOTA coupling effect based method Tagtag.
Publisher
Association for Computing Machinery (ACM)
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