Target-Mounted IRS for Location and Orientation Estimation

Intelligent reflecting surface (IRS) has been widely recognized as an efficient technique to reconfigure the electro-magnetic environment in favor of wireless communication performance. In this paper, we propose a new application of IRS for device-free target sensing via joint location and orientation estimation. In particular, different from the existing works that use IRS as an additional anchor node for localization/sensing, we consider mounting IRS on the sensing target, thus estimating the IRS's location and orientation as that of the target by leveraging IRS's controllable signal reflection. To this end, we first propose a three-dimensional beam training method to acquire essential angle information between the IRS and the sensing transmitter as well as a set of distributed sensing receivers. Next, based on the estimated angle information, we formulate two optimization problems to estimate the location and orientation of the IRS/target, respectively, which are solved by invoking the Taylor-series expansion and manifold optimization. Simulation results show that the proposed method can achieve high estimation accuracy and draw useful insights into the performance of target-mounted IRS sensing systems.