A recently developed published approach to predict echo statistics is applied to clutter data that were collected with a midfrequency sonar and published in a separate independent study. This method explicitly accounts for the (finite) number of unresolved scatterers, the statistics associated with the arbitrary scattering properties of the individual scatterers [but assumed to have identical echo probability density functions (pdfs) in this application], and beampattern effects which significantly affect the echo statistics due to each scatterer being randomly located in the sonar beam. The data had been categorized according to whether they were associated with bottom structures, diffuse compact clutter, and compact nonstationary (moving) clutter. In this paper, the recently developed method is incorporated in a two-component mixed pdf (mixed with a Rayleigh distribution to account for the diffuse background) to model the statistics of the three classes of clutter. This is the first such application of the model which had principally been validated only numerically. The degree to which the data are non-Rayleigh (heavy tailed) is reasonably predicted by the model and the number of scatterers per resolution cell is inferred for each type of clutter.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.