Two-dimensional line spectrum estimation by polar coordinate ar models

Abstract

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 orthogonal coordinate system, such a coordinate system is naturally used for linear prediction in a conventional AR estimation method. The support of the estimation coefficients and the peak shape of the corresponding estimation spectrum are known to be related by a certain rule. By using an AR model in which the coordinate arrangement of the linear prediction is in a polar coordinate, the rotation of the coordinate region keeps an AR model in the same polar coordinate form. Hence, it is possible to determine the relative positional relationship between the estimated spectrum shape and the coefficient mask. It is shown that the present method can estimate the spectrum with a high resolution by using this relationship and avoiding the interference between the spectral peaks.