3D Multi-Target Localization via Intelligent Reflecting Surface: Protocol and Analysis

With the emerging environment-aware applications, ubiquitous sensing is expected to play a key role in future networks. In this paper, we study a 3-dimensional (3D) multi-target localization system where multiple intelligent reflecting surfaces (IRSs) are applied to create virtual line-of-sight (LoS) links that bypass the base station (BS) and targets. To fully unveil the fundamental limit of IRS for sensing, we first study a single-target-single-IRS case and propose a novel two-stage localization protocol by controlling the on/off state of IRS. To be specific, in the IRS-off stage, we derive the Cramér-Rao bound (CRB) of the azimuth/elevation direction-of-arrival (DoA) of the BS-target link and design a DoA estimator based on the MUSIC algorithm. In the IRS-on stage, the CRB of the azimuth/elevation DoA of the IRS-target link is derived and a simple DoA estimator based on the on-grid IRS beam scanning method is proposed. Particularly, the impact of echo signals reflected by IRS from different paths on sensing performance is analyzed and we show that only the signal passing through the BS-IRS-target link is required while that of the BS-target link can be neglected provided that the number of BS antennas is sufficiently large and the dedicated sensing beam at the BS is aligned with the departure transmit array response from the BS to the IRS. Moreover, we prove that the single-beam of the IRS is not capable of sensing, but it can be achieved with multi-beam. Based on the two obtained DoAs, the 3D single-target location is constructed. We then extend to the multi-target-multi-IRS case and propose an IRS-adaptive sensing protocol by controlling the on/off state of multiple IRSs, and a multi-target localization algorithm is developed. Simulation results demonstrate the effectiveness of our scheme and show that sub-meter-level positioning accuracy can be achieved.