Acoustic source localization with environmental uncertainty
Keywords:Error analysis, Gaussian noise (electronic), Nonlinear systems, Numerical analysis, Oceanography, Parameter estimation, Surface properties, Environmental parameters, Gaussian errors, Numerical propagation
AbstractA nonlinear Bayesian formulation is applied to study uncertainty in ocean acoustic source localization due to uncertainty in the knowledge of ocean environmental properties. Localization uncertainty is quantified in terms of probability ambiguity surfaces (PAS), which consists of joint marginal probability distributions for source range and depth integrated over uncertain environmental parameters. Localization uncertainty is considered as a function of the level of uncertainty the prior information for environmental properties. The acoustic data used in the Bayesian focalization consists of the complex pressure recorded at a single frequency of 300Hz, with random Gaussian-distributed errors added to the measured data to reduce the SNR to -3 dB. The data uncertainties, in addition to the additive Gaussian errors, also include theory error resulting from the limitations of the model parameterization and numerical propagation model.
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