A separable 2-D autoregressive spectral estimation algorithm

Abstract

In this paper, a direct-data, 2-D spectral estimation technique is presented, in which the 1-D autoregressive properties of the data are exploited independently in both dimensions. For 2-D, multiple complex sinusoids in white noise, a significant improvement in 2-D resolution is obtained.