### ASA 127th Meeting M.I.T. 1994 June 6-10

## 4pUW5. Environmental data assimilation in matched-field processing with a
random normal mode model.

**Jeffrey L. Krolik
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*Dept. of Elec. Eng., Duke Univ., Box 90291, Durham, NC 27708
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Numerical acoustic propagation models used in matched-field processing
typically assume that ocean environmental parameters, such as the
range-dependent sound-speed profile, are either known exactly or are
characterized by stationary prior statistics. However, neither of these
modeling approaches is well suited for accurately assimilating measurements of
the correct ocean realization into the calculation of point-source acoustic
wave front statistics. In this paper, environmental data is assimilated into a
random adiabatic normal mode propagation model by calculating the conditional
correlation matrix of an acoustic wave front given a set of contemporaneous
sound-speed profile measurements made at different points in space. First-order
perturbation theory is used to map the conditional statistics of
Gaussian-distributed excess sound-speed variations into an estimate of the
conditional point-source wave front correlation matrix. Minimum variance
beamforming with environmental perturbation constraints [J. L. Krolik, J.
Acoust. Soc. Am. 92, 1408--1419 (1992)] conditioned on current environmental
measurements is demonstrated as a means of exploiting this random wave front
model to achieve improved matched-field source localization performance. [Work
supported by ONR.]