  In this brief paper, we propose a time-domain data-driven method for model
order reduction by two-sided moment matching for linear systems. An algorithm
that asymptotically approximates the matrix product $\Upsilon \Pi$ from
time-domain samples of the so-called two-sided interconnection is provided.
Exploiting this estimated matrix, we determine the unique reduced-order model
of order $\nu$, which asymptotically matches the moments at $2 \nu$ distinct
interpolation points. Furthermore, we discuss the impact that certain
disturbances and data distortions may have on the algorithm. Finally, we
illustrate the use of the proposed methodology by means of a benchmark model.
