Time-frequency analysis with Bayesian filtering methods for dispersion tracking

Iterative and sequential Bayesian filtering methods have been previously used in dispersion tracking for long range sound propagation in oceanic environments. In this work we combine previous approaches to develop an improved tracking methods, which will then be used to link the extracted time-frequency information to geoacoustic inversion. The main idea is that probability density functions and Maximum a Posteriori estimates computed for frequencies and arrival times via filtering are propagated "backwards" trough sound propagation models for geoacoustic inversion and quantification of the uncertainty in the estimation process.