High-frequency volume and boundary acoustic backscatter fluctuations in shallow water

Abstract

Volume and boundary acoustic backscatter envelope fluctuations are characterized from data collected by the Toroidal Volume Search Sonar (TVSS), a 68 kHz cylindrical array capable of 360 degrees multibeam imaging in the vertical plane perpendicular to its axis. The data are processed to form acoustic backscatter images of the seafloor, sea surface, and horizontal and vertical planes in the volume, which are used to attribute nonhomogeneous spatial distributions of zooplankton, fish, bubbles and bubble clouds, and multiple boundary interactions to the observed backscatter amplitude statistics. Three component Rayleigh mixture probability distribution functions (PDFs) provided the best fit to the empirical distribution functions of seafloor acoustic backscatter. Sea surface and near-surface volume acoustic backscatter PDFs are better described by Rayleigh mixture or log-normal distributions, with the high density portion of the distributions arising from boundary reverberation, and the tails arising from nonhomogeneously distributed scatterers such as bubbles, fish, and zooplankton. PDF fits to the volume and near-surface acoustic backscatter data are poor compared to PDF fits to the boundary backscatter, suggesting that these data may be better described by mixture distributions with component densities from different parametric families. For active sonar target detection, the results demonstrate that threshold detectors which assume Rayleigh distributed envelope fluctuations will experience significantly higher false alarm rates in shallow water environments which are influenced by near-surface microbubbles, aggregations of zooplankton and fish, and boundary reverberation.

Broadband classification and statistics of echoes from aggregations of fish measured by long-range, mid-frequency sonar

“…23 and references within) and two-component Rayleigh-mixture distributions (e.g., Refs. [35][36][37].…”

Broadband and statistical characterization of echoes from random scatterers : application to acoustic scattering by marine organisms

“…Statistical analysis of data usually involves fitting the data to a large pool of models to determine the best representation (e.g., Abraham and Lyons, 2010;Gallaudet and de Moustier, 2003;La Cour, 2004;Watts and Wards, 2010). However, since most of these models do not provide explicit connections between the model parameters and the underlying scattering mechanisms, statistical descriptions using this datadriven approach are often only applicable to data collected using similar systems in specific geographical locations.…”

“…3-1(a)], the multiple-component mixture model (referred to as the "M -component mixture model" throughout this paper) has been used extensively to fit experimental data (e.g., Abraham et al, , 2011Chotiros, 2010;Gallaudet and de Moustier, 2003;Ward and Tough, 2002). This model describes the echo distribution as a linear combination of multiple probability distributions through where N m and r m are the number of scatterers and relative scattering amplitude, respectively, of the mth type of scatterer.…”

Non-Rayleigh Acoustic Scattering Characteristics of Individual Fish and Zooplankton

“…For the cases in which they are not resolved, the echoes from the group echo would be further complicated by the additive effects of the individual echoes. In addition to the influence of the physics of the scattering as described in this paper, the group echo would also depend upon the number of organisms within a resolution cell as well as their average separation, degree of spatial heterogeneity (i.e., patchiness), and size distribution (see, for example, [5] and [6]). …”