Environmental uncertainty in ocean acoustic source localization

Localization of an acoustic source in the ocean is often limited by lack of knowledge of the physical properties of the environment, such as seabed geoacoustic parameters and water-column sound-speed profile (SSP). Quantifying environmental uncertainties and how they transfer to uncertainties for source localization represent important problems that are addressed in this paper using Bayesian inference theory. Metropolis Gibbs' sampling is applied to estimate the uncertainties for environmental inversion in the form of marginal probability distributions, covariances and credibility intervals. Heat-bath sampling is applied to source localization with environmental uncertainties, with the resulting localization uncertainty quantified in terms of the joint marginal probability distribution for source range and depth (i.e. a probability ambiguity surface). Localization uncertainties are examined as a function of uncertainties in geoacoustic parameters and SSP.