Stable nonlinear methods for sensor array processing;

Most nonlinear high-resolution bearing estimators are unstable in the presence of correlated noise, system phase errors, and multipath arrivals because they inadvertently place too much emphasis on unstable eigenvectors of the cross-sensor correlation matrix. For moderately correlated noise there will be sufficiently many stable eigenvectors to resolve and localize discrete sources. A method is given (the "stable nonlinear method" or SNLM) whereby reweighting of the eigenvectors is achieved implicitly, without actual calculation of the eigenvectors. This SNLM is compared with Capon\´s maximum likelihood method (MLM) in simulations of correlated noise, partially correlated signals, and phase errors, and is shown to provide good stability in the cases considered.