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Intelligent reflecting surface (IRS) has been widely recognized as anefficient technique to reconfigure the electromagnetic environment in favor ofwireless communication performance. In this paper, we propose a new applicationof IRS for device-free target sensing via joint location and orientationestimation. In particular, different from the existing works that use IRS as anadditional anchor node for localization/sensing, we consider mounting IRS onthe sensing target, whereby estimating the IRS's location and orientation asthat of the target by leveraging IRS's controllable signal reflection. To thisend, we first propose a tensor-based method to acquire essential angleinformation between the IRS and the sensing transmitter as well as a set ofdistributed sensing receivers. Next, based on the estimated angle information,we formulate two optimization problems to estimate the location and orientationof the IRS/target, respectively, and obtain the locally optimal solutions tothem by invoking two iterative algorithms, namely, gradient descent method andmanifold optimization. In particular, we show that the orientation estimationproblem admits a closed-form solution in a special case that usually holds inpractice. Furthermore, theoretical analysis is conducted to draw essentialinsights into the proposed sensing system design and performance. Simulationresults verify our theoretical analysis and demonstrate that the proposedmethods can achieve high estimation accuracy which is close to the theoreticalbound.

Target-Mounted Intelligent Reflecting Surface for Joint Location and Orientation Estimation