RF-UI: Continuous User Identification Through Gaits Using RFID

Abstract

Continuous user identification could facilitate large-scale identity-based services, potentially including access control, security management, personalized services, and beyond. Although current RFID-based user identification systems demonstrate effective performance in single-user scenarios, they exhibit a lack of robustness and accuracy when extended to multi-user environments. In this paper, we propose RF-UI, a low-cost continuous user identification system that can tolerate different interference factors (e.g., appearance changes, inconsistent walking paths). The intuition underlying our design is that when multiple users traverse the radio gate sequentially, the received signal is dominated by the user traversing the radio gate. We develop an algorithm that utilizes phase energy fluctuation to separate signals from different users and extract valid gait-related patterns by applying neighborhood energy sliding windows. Then, we construct a Joint Similarity Matrix (JSM) for characterizing gait features that are robust against various interference factors. Finally, RF-UI achieves cost-effective data augmentation through the deployment of only a few additional tags. Extensive experiments show that RF-UI achieved an accuracy of 94% under various interference factors and maintained a high accuracy of 92.8% in continuous user identification.