The robust covariation-based MUSIC (ROC-MUSIC) algorithm for bearing estimation in impulsive noise environments

This paper presents a new subspace-based method for bearing estimation in the presence of impulsive noise which can be modeled as a complex symmetric alpha-stable (S alpha S) process. We define the covariation matrix of the array sensor outputs and show that eigendecomposition-based methods, such as the MUSIC algorithm, can be applied to the sample covariation matrix to extract the bearing information from the measurements. A consistent estimator for the marginals of the covariation matrix is presented and its asymptotic performance is studied. The improved performance of the proposed source localization method in the presence of a wide range of impulsive noise environments is demonstrated via Monte Carlo experiments.