New spectral positional invariance approach for superresolution of point-type targets embedded in colored noise

A new technique is proposed for high-resolution spectral estimation of point-type targets in multi-grade background scenes. All existing spectral estimation methods operating with short data lengths face the contradiction of providing superresolution of the spectral components related to distinct signal sources, and the smoothed reconstruction of the spectral shape of the extended component as a whole. The method addressed here implies considering the spectrum estimation problem under two paradigms: (i) the Prony estimation of the point-type targets; (ii) the nonparametric maximum entropy estimation applied to reconstruct the image of the background scene. By fusing these two methods, we achieve a substantial improvement in resolutions of point-type targets as well as the background spectral characterization.