Effects of multiple scattering, attenuation and dispersion in waveguide sensing of fish

J Acoust Soc Am. 2011 Sep;130(3):1253-71. doi: 10.1121/1.3614542.

Abstract

An ocean acoustic waveguide remote sensing system can instantaneously image and continuously monitor fish populations distributed over continental shelf-scale regions. Here it is shown theoretically that the areal population density of fish groups can be estimated from their incoherently averaged broadband matched filtered scattered intensities measured using a waveguide remote sensing system with less than 10% error. A numerical Monte-Carlo model is developed to determine the statistical moments of the scattered returns from a fish group. It uses the parabolic equation to simulate acoustic field propagation in a random range-dependent ocean waveguide. The effects of (1) multiple scattering, (2) attenuation due to scattering, and (3) modal dispersion on fish population density imaging are examined. The model is applied to investigate population density imaging of shoaling Atlantic herring during the 2006 Gulf of Maine Experiment. Multiple scattering, attenuation and dispersion are found to be negligible at the imaging frequencies employed and for the herring densities observed. Coherent multiple scattering effects, such as resonance shifts, which can be significant for small highly dense fish groups on the order of the acoustic wavelength, are found to be negligible for the much larger groups typically imaged with a waveguide remote sensing system.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Acoustics*
  • Air Sacs / physiology
  • Animals
  • Computer Simulation
  • Environmental Monitoring / methods*
  • Fishes / physiology*
  • Models, Theoretical
  • Monte Carlo Method
  • Motion
  • Numerical Analysis, Computer-Assisted
  • Oceans and Seas
  • Population Density*
  • Scattering, Radiation
  • Signal Processing, Computer-Assisted*
  • Sound Spectrography
  • Sound*
  • Time Factors