A robust interpolation algorithm for spectral estimation

We propose a robust interpolation algorithm for model-based spectral estimation. The interpolation data represent information about the half spectrum function associated with a given signal and are computed from an input-to-state filter. Our algorithm allows a large number of noisy interpolation data to be used to optimally fit a half spectrum function of a fixed order. The algorithm involves solving a set of linear matrix inequalities and is thus numerically efficient.