High-frequency side-scan sonar fish reconnaissance by autonomous underwater vehicles

Author:

Grothues Thomas M.1,Newhall Arthur E.2,Lynch James F.2,Vogel Kaela S.3,Gawarkiewicz Glen G.4

Affiliation:

1. Rutgers University Marine Field Station, 800 c/o 132 Great Bay Blvd., Tuckerton, NJ 08087, USA.

2. Woods Hole Oceanographic Institution, Applied Ocean Physics and Engineering Dept., 266 Woods Hole Rd., MS# 11, Woods Hole, MA 02543-1050, USA.

3. Department of Marine Biology, University of North Carolina Wilmington, Wilmington, NC 28701, USA.

4. Woods Hole Oceanographic Institution, Physical Oceanography Dept., 266 Woods Hole Rd., MS# 21, Woods Hole, MA 02543-1050, USA.

Abstract

A dichotomy between depth penetration and resolution as a function of sonar frequency, draw resolution, and beam spread challenges fish target classification from sonar. Moving high-frequency sources to depth using autonomous underwater vehicles (AUVs) mitigates this and also co-locates transducers with other AUV-mounted short-range sensors to allow a holistic approach to ecological surveys. This widely available tool with a pedigree for bottom mapping is not commonly applied to fish reconnaissance and requires the development of an interpretation of pelagic reflective features, revisitation of count methods, image-processing rather than wave-form recognition for automation, and an understanding of bias. In a series of AUV mission test cases, side-scan sonar (600 and 900 kHz) returns often resolved individual school members, spacing, size, behavior, and (infrequently) species from anatomical features and could be intuitively classified by ecologists — but also produced artifacts. Fish often followed the AUV and thus were videographed, but in doing so removed themselves from the sonar aperture. AUV-supported high-frequency side-scan holds particular promise for survey of scarce, large species or for synergistic investigation of predators and their prey because the spatial scale of observations may be similar to those of predators.

Publisher

Canadian Science Publishing

Subject

Aquatic Science,Ecology, Evolution, Behavior and Systematics

Reference86 articles.

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3. Belbachir, A., Lacroix, S., Ingrand, F., Perrier, M., and Opderbecke, J. 2010. Cooperative-adaptive algorithms for targets localization in underwater environment. Autonomous Underwater Vehicles (AUV). IEEE/OES.1-7 10.1109/AUV. 2010.5779650.

4. Bell, R.E., Flood, R.D., Carbotte, S., Ryan, W.B.F., McHugh, C., Cormier, M., Versteeg, R., Bokuniewicz, H., Ferrini, V.L., Thissen, J., Ladd, J.W., and Blair, E.A. 2006. Benthic habitat mapping in the Hudson River Estuary. In The Hudson River Estuary. Edited by J. Levinton and John R.W. Cambridge. University Press, Cambridge, England. pp. 51–64.

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