IMIS | Flanders Marine Institute

Flanders Marine Institute

Platform for marine research


Publications | Institutes | Persons | Datasets | Projects | Maps
[ report an error in this record ]basket (0): add | show Printer-friendly version

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.
In: The Journal of the Acoustical Society of America. American Institute of Physics: New York. ISSN 0001-4966, more
Peer reviewed article  

Available in  Authors 
Document type: Summary

Authors  Top 
  • Siemes, K.
  • Snellen, M.
  • Simons, D.G.
  • Hermand, J.-P., more
  • Meyer, M.
  • Le Gac, J.-C.

    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.

All data in IMIS is subject to the VLIZ privacy policy Top | Authors