Frequency domain subspace-based identification of discrete-time singular power spectra

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.

► We propose a subspace identification algorithm for LTI systems from measured singular spectra.
► The proposed algorithm is consistent when measurement errors are covariance-bounded.
► Asymptotic performance of the algorithm is illustrated by a numerical example.