Robust maximum likelihood source localization by exploiting predictable acoustic modes

This paper presents a robust maximum-likelihood estimator for matched-field source localization in the presence of uncertainties in the ocean environment. The method is based on a decomposition of the field into predictable and unpredictable subspaces of the acoustic normal mode representation. The performance of the method is evaluated and compared to other matched-field methods using simulations and acoustic array data from the Mediterranean Sea. The algorithm has superior probability of correct localization than the maximum-likelihood, matched-mode-processing, and Bartlett methods