2-DIMENSIONAL LINE SPECTRUM ESTIMATION BY POLAR COORDINATE AR MODELS

In this paper, a spectrum estimation method is proposed which is based on a two-dimensional autoregressive (AR) model with polar coordinate coefficient arrangement. When the signal is given in terms of an ortho gonal coordinate system, such a coordinate system is naturally used fo r linear prediction in a conventional AR estimation method. The suppor t of the estimation coefficients and the peak shape of the correspondi ng estimation spectrum are known to be related by a certain rule. By u sing an AR model in which the coordinate arrangement of the linear pre diction is in a polar coordinate, the rotation of the coordinate regio n keeps an AR model in the same polar coordinate form. Hence, it is po ssible to determine the relative positional relationship between the e stimated spectrum shape and the coefficient mask. It is shown that the present method can estimate the spectrum with a high resolution by us ing this relationship and avoiding the interference between the spectr al peaks.