2-D spectral estimation combining parametric estimation of background and maximum entropy estimation

A new algorithm for the estimation of the two-dimensional (2-D) power spectrum from finite correlation data is proposed. This method is based on the combination of parametric estimation of a background power spectral component and maximum entropy estimation for point-like spectral components. For the discrimination of the background power spectrum, we adopt a new measure which reflects the information of the point-like spectral components. A practical iterative algorithm is presented and the effectiveness of the method is demonstrated through several numerical examples.