We investigate reconfigurable intelligent surfaces (RISs) for the task of position and velocity estimation in non-LOS (NLOS) indoor scenarios, using a snapshot based multi-step estimation algorithm. We evaluate a compound RIS structure prototype composed of four RIS tiles with 1-bit phase control per RIS unit cell. Numerical simulation results taking the antenna patterns into account are presented for an 3 m x 3 m area of interest. We demonstrate that the initial grid search step using the far field assumption is not robust enough for small distances to the RIS center and propose a more robust algorithm. Furthermore, we show that the effect of the antenna pattern causes an increased position and velocity error. Our modified three-step algorithm achieves a position error of 7 mm and a velocity error of 0.12 m/s at a distance of 2 m to the RIS center under a realistic numerical propagation model.
@article{arxiv.2602.12979,
title = {RIS Nearfield Position and Velocity Estimation Using a Validated Propagation Model},
author = {Thomas Zemen and Musa Furkan Keskin and Moustafa Rahal and Thomas Wilding and Hamed Radpour and Markus Hofer and Benoit Denis and Henk Wymeersch},
journal= {arXiv preprint arXiv:2602.12979},
year = {2026}
}
Comments
5 pages, 5 figures, accepted for European Conference on Antennas and Propagation (EuCAP), Dublin, Ireland, April 2025