Hybrid and Passive RIS Enabled High Precision Indoor Localization

Accurate indoor wireless localization remains a challenging task, particularly in non-line-of-sight (NLOS) environments where signal attenuation, multipath effects, and physical obstructions degrade localization performance. Reconfigurable intelligent surfaces (RIS) provides a promising solution by creating virtual line-of-sight (LoS) paths, thereby improving the localization accuracy in complex indoor scenarios. This paper investigates a hybrid and passive RIS enabled localization approach, where the active elements of the hybrid RIS are employed to estimate the angle of arrival (AOA), while base stations (BS) leverage the received signals to estimate the time difference of arrival (TDOA) among different RISs. This paper proposes a localization scheme by jointly utilizing the estimated TDOA and AOA information, significantly enhancing the accuracy of indoor localization. Simulation results show that the proposed localization algorithm achieves centimeter-level accuracy, offering a feasible solution for indoor localization.