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01703nam a2200325Ia 4500 |
| 001 |
10.1121-1.5126351 |
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220511s2019 CNT 000 0 und d |
| 020 |
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|a 00014966 (ISSN)
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| 245 |
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|a A computational Bayesian approach for localizing an acoustic scatterer in a stratified ocean environment
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| 260 |
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|b Acoustical Society of America
|c 2019
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| 856 |
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|z View Fulltext in Publisher
|u https://doi.org/10.1121/1.5126351
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| 520 |
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|a A computational Bayesian method is presented for inference regarding the state of a submerged mobile object. The approach addresses the challenge of closely spaced multipath arrivals in refractive environments with uncertainty in ambient acoustic noise power. Vertical angles and Doppler frequencies of the arrival returns are jointly inferred and their posterior density is mapped to the object's range, depth, and speed through acoustic ray interpolation. The object is localized under the challenging constraint of a small receive vertical aperture. A case study with the classic Munk sound speed profile is presented to lend credence to the approach. © 2019 Acoustical Society of America.
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|a Acoustic noise
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| 650 |
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|a article
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|a Bayesian approaches
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|a Bayesian methods
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| 650 |
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|a Bayesian networks
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| 650 |
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|a Doppler frequency
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| 650 |
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|a Mobile objects
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| 650 |
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|a Multipath
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| 650 |
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|a noise
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| 650 |
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|a ocean environment
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| 650 |
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|a Sound speed profiles
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| 650 |
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|a Stratified ocean
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|a uncertainty
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|a Underwater acoustics
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|a velocity
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|a Barros, A.C.
|e author
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|a Gendron, P.J.
|e author
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| 773 |
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|t Journal of the Acoustical Society of America
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