5G and Beyond: An EKF-Based Reconfigurable Intelligent Surface (RIS)-Aided Navigation Approach

Ali A. Abdallah and A. Lee Swindlehurst

Peer Reviewed

Abstract:	A novel extended Kalman filter (EKF)-based reconfigurable intelligent surface (RIS)-aided navigation approach in a millimeter-wave uplink cellular environment is developed. The proposed approach presents a newly developed measurement engine for estimating the time-of-arrival (TOA) and angle-of-arrival (AOA) from the uplink received signal, leveraging a passive correlation-based approach for AOA estimation. A Monte Carlo analysis is conducted to highlight the estimation accuracy of the proposed AOA estimator. Furthermore, an EKF-based framework is introduced to estimate the three-dimensional (3D) position and velocity of a mobile user-equipment (UE), based on which the RIS phase profile is then optimized to maximize the signal-to-noise ratio (SNR) for the various UEs. This paper concludes with a demonstration of navigation solution accuracy via Monte Carlo simulations across various platforms: pedestrians, ground vehicles, and unmanned aerial vehicles (UAVs), underscoring the practicality and utility of the proposed navigation system in achieving a sub-meter-level and meter-level positioning accuracies for 2D and 3D, respectively.
Published in:	Proceedings of the 36th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2023) September 11 - 15, 2023 Hyatt Regency Denver Denver, Colorado
Pages:	2348 - 2360
Cite this article:	Abdallah, Ali A., Swindlehurst, A. Lee, "5G and Beyond: An EKF-Based Reconfigurable Intelligent Surface (RIS)-Aided Navigation Approach," Proceedings of the 36th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2023), Denver, Colorado, September 2023, pp. 2348-2360. https://doi.org/10.33012/2023.19234
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