Passive localization in ocean acoustics: A model-based approach

Abstract

A model-based approach is developed to solve the passive localization problem in ocean acoustics using the state-space formulation for the first time. It is shown that the inherent structure of the resulting processor consists of a parameter estimator coupled to a nonlinear optimization scheme. The parameter estimator is designed using the model-based approach in which an ocean acoustic propagation model is used in developing the model-based processor required for localization. Recall that model-based signal processing is a well-defined methodology enabling the inclusion of environmental (propagation) models, measurement (sensor arrays) models, and noise (shipping, measurement) models into a sophisticated processing algorithm. Here the parameter estimator is designed, or more appropriately the model-based identifier (MBID) for a propagation model developed from a shallow water ocean experiment. After simulation, it is then applied to a set of experimental data demonstrating the applicability of this approach.