The USC Andrew and Erna Viterbi School of Engineering USC Signal and Image Processing Institute USC Ming Hsieh Department of Electrical Engineering University of Southern California

Technical Report USC-SIPI-278

“The Robust Covariation-Based MUSIC (ROC-MUSIC) Algorithm for Bearing Estimation in Impulsive Noise Environments”

by Panagiotis Tsakalides and Chrysostomos L. Nikias

January 1995

This report 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_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. Consistent estimators for the covariation matrix are presented, and their asymptotic performance is studied through both theory and simulations. 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.

To download the report in PDF format click here: USC-SIPI-278.pdf (4.3Mb)