Reconfigurable intelligent surface (RIS) has been recognized as a promising solution for enhancing localization accuracy. Traditional RIS-based localization methods typically rely on prior channel knowledge, beam scanning, and pilot-based assistance. These approaches often result in substantial energy and computational overhead, and require real-time coordination between the base station (BS) and the RIS. In this work, we propose a novel multiple RISs aided localization approach to address these challenges. The proposed method first estimates the angle-of-directions (AoDs) between the RISs and the user using the conditional sample mean approach, and then uses the estimated multiple AoD pairs to determine the user's position. This approach only requires measuring the received signal strength at the BS for a set of randomly generated phase shifts across all RISs, thereby eliminating the need for real-time RIS phase shift design or user-to-BS pilot transmissions. Numerical results show that the proposed localization approach improves localization accuracy while significantly reducing energy and signaling overhead compared to conventional methods.

翻译：可重构智能表面（RIS）已被公认为提升定位精度的有效解决方案。传统基于RIS的定位方法通常依赖于先验信道知识、波束扫描以及基于导频的辅助。这些方法往往导致巨大的能量与计算开销，且需要基站（BS）与RIS之间的实时协调。本文提出一种新型多RIS辅助定位方法以应对这些挑战。所提方法首先利用条件样本均值法估计RIS与用户之间的离角（AoD），随后利用估计得到的多组AoD对确定用户位置。该方法仅需测量基站处针对所有RIS随机生成相位偏移集合的接收信号强度，从而无需实时设计RIS相位偏移或进行用户至基站的导频传输。数值结果表明，与传统方法相比，所提定位方法在显著降低能量与信令开销的同时，提升了定位精度。