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 a key
interpolation matrix from time-domain samples of the so-called two-sided interconnection is provided.
Exploiting this estimated interpolation matrix, we determine the unique reduced-order model of order
ν, which asymptotically matches the moments at 2ν 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.