### ASA 129th Meeting - Washington, DC - 1995 May 30 .. Jun 06

## 1aAO10. Ray identification theory in ocean acoustic tomography.

**D. Mauuary
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*Inst. Fur Meereskunde, Dusternbrooker Weg 20, D-24143 Kiel, Germany
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The identification problem in multipath ocean acoustic tomography is not
only one of the more crucial but also one of the more difficult signal
processing problems to solve for further inverse studies. It is only recently
that a tool, based on the Bayesian decision theory and close to the data
association problem in RADAR, has been proposed by Mauuary and Moura. It
fundamentally uses prior information ocean variability which transits through
the ray acoustic model. It also statistically solves the ray identification
problem with a Bayesian strategy. Despite the inherent complexity of resulting
algorithms, a first successful attempt has been made on a French tomographic
set of data (GASTOM). Some simplifications and further experimental use are now
being investigated on the Mediteranean set of data (THETIS). With another
approach given by Send, those are the only practical tools, but, they are
sufficiently general to solve the identification problem in the most difficult
conditions given by unresolved and unstable data. Both solutions are very close
to the generalized Kalman filter theory and joint use of these algorithms in
data assimilation models can be expected.