RIS-Based DOA Estimation for Communication-Assisted Sensing Systems Under Hardware Impairments

Abstract

Reconfigurable intelligent surface (RIS)-based localization has received significant attention in wireless communication systems due to its potential for enabling non-line-of-sight (NLoS) wireless sensing. However, hardware impairments (HWIs) in non-ideal hardware adversely affect the localization performance. To address the issue, this work studies a RIS-aided passive sensing system with the presence of HWIs, where communications signals are used to sense targets. We propose a method to address a DOA estimation problem in three-dimensional (3D) space. Specifically, a low-rank matrix is first recovered by solving an atomic norm minimization (ANM) problem, which is not affected by interference signal and additive noise. Subsequently, a block Hankel matrix is constructed using the correlation information of the low-rank matrix. The elevation and azimuth angles between targets and RIS are then estimated by applying the modified matrix pencil (MMP) method on the block Hankel matrix. We also derive the Cramér-Rao Bound (CRB) with closed-form expressions for DOA estimation based on the proposed system model. The proposed algorithm can sense multiple targets and achieve parameter automatic pairing. Numerical results verify the superiority of the proposed algorithm over the traditional schemes.