Most reliable null space vector and its application to direction finding

摘要

Given a data matrix, we desire a null space vector that is the most robust against correlated Gaussian noise perturbations. In this paper, a closed-form calculation of the most reliable null space vector is presented. An attempt to modify the Mm-Norm direction finding algorithm for use in spatio-temporal colored noise is investigated.