An improved maximum likelihood method for power spectral density estimation

In this paper, we present a new procedure for spectral analysis; it represents a tradeoff between the high resolution provided by the maximum entropy method (MEM) and the low sidelobe characteristic of the maximum likelihood method (MLM). The approach that we follow is to introduce a slight modification of the second technique to obtain from the ML filter the true spectral density, not the power level as the original procedure does. The proposed method can be used both in one-dimensional and two-dimensional problems without a remarkable increase of computational load relative to the original MLM.