Intelligent Reflecting Surface-Assisted Combined TOA and AOA Localization Algorithm

Wireless positioning technology plays a crucial role in various applications, including intelligent transportation, industrial automation, and smart cities.However, in non-line-ofsight environments, signal obstruction and multipath effects significantly degrade localization accuracy.To address these challenges, this paper proposes an Intelligent Reflecting Surfaceassisted Combined time of arrival (TOA) and angle of arrival (AOA) Localization (IRS-CTAL) algorithm.Specifically, this paper introduces a dynamic partially connected IRS structure, which selectively activates IRS sub-arrays in a time-division manner.This dynamic activation mitigates multipath interference and enhances the controllability of IRS-reflected signals, leading to improved localization performance.In the proposed IRS-CTAL algorithm, the 2D multiple signal classification algorithm is employed to jointly estimate the TOA and AOA of the received signals.Furthermore, to optimize the estimated coordinates and minimize the localization error, this paper incorporates the root mean square propagation algorithm, which efficiently corrects nonlinear distortions caused by IRS reflections.Simulation results demonstrate that the IRS-CTAL algorithm significantly outperforms traditional localization methods, achieving an average localization error reduction of 41% compared to the direct geometric computation method.