An iterative algorithm for robust 2-D spectrum estimation

Most of the parametric techniques of the spectrum estimation assume a specific distribution for the observations. Even a small number of outliers in the observations, violating the distribution assumption can yield poor spectral estimates. We present an algorithm which yields 2-D spectral estimates, robust to additive outliers. The algorithm is iterative in nature and involves fitting a 2-D noncausal spatial autoregressive (SAR) to the given data.