Frequency domain subspace-based identification of discrete-time singular power spectra from uniformly spaced measurements

In this paper, we propose a subspace algorithm for the identification of linear-time-invariant discrete-time systems with more outputs than inputs from measured power spectrum data. The proposed identification algorithm is interpolatory and strongly consistent when the corruptions in the spectrum measurements have a bounded covariance function. Asymptotic performance and the interpolation properties of the proposed algorithm are illustrated by means of a numerical example.