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Multibeam echosounder water column data provides a three-dimensional image of features between the water surface and the seafloor. Although this swath of acoustic data can be collected over a wide range of angles, most of the data, at least beyond the range to the first seafloor return, is contaminated by noise created by receiver array sidelobe interference. As a result, the water column data beyond the minimum slant range commonly is excluded from analysis. This paper demonstrates a method to consistently filter and extract targets comprising a gas seep feature across the multibeam swath, including targets within the areas dominated by receiver array sidelobe interference. For each sample range, data are filtered based on the mean plus a certain number (k) of standard deviations of the sample values along that range. The filtering is coupled with a morphological classification to retain only targets of interest while excluding background data and noise. Data were collected over a shallow water artificial gas seep using two different flow rates and at three different vessel speeds. Using the proposed method, 119 of 124 test seeps were identified correctly. Seep targets were identified at all angles across the water column fan up to beam pointing angles of 55°, with 19 of 23 seeps being correctly identified at angles greater than 50°. This method demonstrates that features can be extracted and geolocated in the sidelobe noise when the interference is appropriately filtered. These results will improve the areal extent of multibeam surveys and increase the utility of acoustic data in capturing information on water column targets directly above the seafloor.

Item Type:	Refereed Article
Keywords:	multibeam echosounder, water column data, sidelobe interference, gas seep detection, automated processing
Research Division:	Engineering
Research Group:	Geomatic engineering
Research Field:	Surveying (incl. hydrographic surveying)
Objective Division:	Environmental Management
Objective Group:	Marine systems and management
Objective Field:	Assessment and management of benthic marine ecosystems
UTAS Author:	Nau, AW (Dr Amy Nau)
UTAS Author:	Ladroit, Y (Dr Yoann Ladroit)
UTAS Author:	Lucieer, V (Dr Vanessa Lucieer)
ID Code:	150921
Year Published:	2022
Deposited By:	Ecology and Biodiversity
Deposited On:	2022-07-05
Last Modified:	2022-07-06
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