In this article we examine time evolution of the a posteriori probability distribution for the source location in an elementary passive sonar model. The approach employs Bayesian inversion to obtain the a posteriori distributions. The resulting multimodal distributions reflect the nonlinear relationship between source location and array output. This probabilistic approach allows us to include a priori information, utilize ocean acoustic modeling, and make direct use of increased data integration time.
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