An efficient maximum entropy technique for 2-D isotropic random fields

A novel linear maximum-entropy method (MEM) spectral-estimation algorithm for 2-D isotropic random fields is presented. This procedure differs from pervious 2-D MEM algorithms by the fact that maximum advantage is taken of the symmetries implied by isotropy. It is shown that the isotropic MEM problem has a linear solution and that it is equivalent to the problem of constructing the optimal linear filter for estimating the underlying isotropic field at a point on the boundary of a disk of radius R, given noisy measurements of the field inside the disk. A fast algorithm for computing the estimation filter is then used to obtain the MEM spectral estimate