A cumulant-based linear prediction (CBLP) method for two-dimensional (2-D) spectral estimation is presented. The main idea of the method is to compute the coefficients of two different single-quadrant prediction filters by applying the LP theory to a selected 2-D fourth-order mixed cumulant slice of the noisy signal. These coefficients are employed in formulating two different autoregressive spectral models. Both spectral models are combined to obtain the desired spectral estimate. The effectiveness of the proposed CBLP method is demonstrated through computer simulation.
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