Reconfigurable Intelligent Surface Assisted User Tracking with Sliding Window in Space-Confined Tunnels
Weijun Cheng, Xiaoxue Ma, Gaofeng Nie · 2024
In recent years, reconfigurable intelligent surface (RIS) assisted localization has garnered significant attention. However, there has been relatively limited research on RIS assisted user tracking, especially in space-confined tunnels. To this end, this paper proposes a novel RIS-assisted user tracking scheme. In this scheme, we first segment a strip-shaped RIS to address the near-field approximation in constrained tunnel environments. Then, we combine a sliding-window RIS with an extended Kalman filter (EKF) for user tracking, where the sliding-window RIS ensures that the user remains within the tracking beam, and the EKF achieves real-time tracking. Finally, numerical results show that the proposed approach achieves effective user mobility tracking and outperforms the traditional tracking scheme in space-confined tunnels.