  Intelligent reflecting surface (IRS) has been widely recognized as an
efficient technique to reconfigure the electromagnetic 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, whereby 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 tensor-based 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, and obtain the locally optimal solutions to
them by invoking two iterative algorithms, namely, gradient descent method and
manifold optimization. In particular, we show that the orientation estimation
problem admits a closed-form solution in a special case that usually holds in
practice. Furthermore, theoretical analysis is conducted to draw essential
insights into the proposed sensing system design and performance. Simulation
results verify our theoretical analysis and demonstrate that the proposed
methods can achieve high estimation accuracy which is close to the theoretical
bound.
