Single Antenna Tracking and Localization of RIS-enabled Vehicular Users

2024-11-23

IEEE Transactions on Vehicular Technology

AI Summary

To address high-precision localization and tracking of mobile targets (e.g., vehicles) in reconfigurable intelligent surface (RIS)-assisted wireless networks, this paper proposes a geometry-driven joint estimation framework leveraging RIS phase-controllable reflection. Employing a single-antenna transmitter and distributed single-antenna receivers, the method models the geometric characteristics of RIS-reflected signals to jointly optimize RIS phase configurations and estimate multi-user time-of-arrival (ToA) and phase shifts. We derive, for the first time, the Cramér–Rao lower bound (CRLB) for mobile users under RIS assistance, explicitly characterizing the performance gain enabled by phase control. Simulation results demonstrate that the proposed approach reduces localization error by up to threefold compared to conventional ToA-based methods, achieving millimeter-level static positioning accuracy and robust dynamic tracking. This significantly enhances the sensing capability of RIS in mobile scenarios.

Technology Category

• Intelligent Robots: Localization, Mapping, and Navigation
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Local Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Location- and context-aware Web and WoT applications and services
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Search and Retrieval-Augmented AI: Personalized, context-aware and across-device search

Abstract

Reconfigurable Intelligent Surfaces (RISs) are envisioned to be employed in next generation wireless networks to enhance the communication and radio localization services. In this paper, we propose novel localization and tracking algorithms exploiting reflections through RISs at multiple receivers. We utilize a single antenna transmitter (Tx) and multiple single antenna receivers (Rxs) to estimate the position and the velocity of users (e.g. vehicles) equipped with RISs. Then, we design the RIS phase shifts to separate the signals from different users. The proposed algorithms exploit the geometry information of the signal at the RISs to localize and track the users. We also conduct a comprehensive analysis of the Cramer-Rao lower bound (CRLB) of the localization system. Compared to the time of arrival (ToA)-based localization approach, the proposed method reduces the localization error by a factor up to three. Also, the simulation results show the accuracy of the proposed tracking approach.

Problem

• Reconfigurable Intelligent Surface
• Wireless Network
• Target Localization and Tracking

Innovation

• RIS-based localization
• multi-antenna reception
• interference avoidance