| one publication added to basket [215871] | High-frequency multibeam echosounder classification for rapid environmental assessment
Siemes, K.; Snellen, M.; Simons, D.G.; Hermand, J.-P.; Meyer, M.; Le Gac, J.-C. (2008). High-frequency multibeam echosounder classification for rapid environmental assessment. J. Acoust. Soc. Am. 123(5): 3622. dx.doi.org/10.1121/1.2934843 In: The Journal of the Acoustical Society of America. American Institute of Physics: New York. ISSN 0001-4966; e-ISSN 1520-8524, more |   |
| Available in | Authors | | Document type: Summary
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| Authors | | Top | - Siemes, K., more
- Snellen, M.
- Simons, D.G.
| - Hermand, J.-P., more
- Meyer, M., more
- Le Gac, J.-C.
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| Abstract | For shallow-water naval operations, obtaining rapidly an accurate picture of the environmental circumstances often is of high importance. Hereto a multi-sensor approach is required. In this context, the MREA/BP'07 experiment has been carried out south of Elba (Mediterranean Sea), where several techniques of environmental characterization covering the fields of underwater acoustics, physical oceanography and geophysics have been combined [Le Gac&Hermand, 2007]. The required information typically concerns water-column properties, sea surface roughness, and sediment geo-acoustic properties. Estimating these geo-acoustic parameters from inversion of acoustic data received on drifting sparse arrays has proved to be a promising approach. Part of MREA/BP'07 was therefore dedicated to this type of measurement. For validating the resulting geo-acoustic estimates sediment samples were collected. Additionally, measurements were carried out using a multibeam-echosounder. This system provides depth information, but also allows for seafloor classification. The classification approach taken is model-based employing the backscatter data. It discriminates between sediments in the most optimal way by applying the Bayes decision rule for multiple hypotheses, implicitly accounting for backscatter-strength ping-to-ping variability. Here, results of seafloor classification using the multibeam data and a preliminary comparison with the sediment sample analysis and the geo-acoustic parameter estimates as obtained from the drifting arrays are presented. |
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