### ASA 124th Meeting New Orleans 1992 October

## 4aUW12. A Bayesian approach to passive acoustic signal processing.

**Richard Pitre
**

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Nolan R. Davis
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**
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*Code 5160, Naval Res. Lab., Washington, DC 20375-5000
*

*
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This work considers a systematic approach to data inversion and data
fusion for stationary passive sonar in low signal-to-noise situations. Bayesian
inversion is applied to the probability distributions that are implicit in
conventional signal processing methods. The resulting source location
probability distributions are multimodal, reflecting the sidelobe structure of
conventional ambiguity functions. Using the probability interpretation of these
distributions the secondary sidelobe peaks can be compared quantitatively with
the mainlobe. Results of model calculations are presented for an ocean
waveguide in order to demonstrate the method, provide a comparison with
conventional approaches, and assess the performance under low signal-to-noise
conditions. A preliminary discussion of data fusion is given for probability
distributions derived from inversion of independent data sets. An application
to frequency fusion is made, and a performance improvement is demonstrated with
the computational model.