Abstract
In the field of seabed sonar imagery, it is necessary to establish local scattering models to improve the performances of the detection or recognition algorithms. In this paper, we present the Probability Density Function (PDF) of the acoustic intensity scattered by a natural profile as a function of the bistatic angle. To do this we have developed a 1-D bistatic scattering model called NEWS (Numerical Estimation for Waves Scattering) that incorporates physical phenomenons like multiple reflections, shadow and the reflection coefficient of the profile. Moreover, NEWS takes into account acquisition parameters like sensors characteristics and their positions in relation to the center of the illuminated area. Gaussian spectra for the profile height fluctuation are considered. Five hundred profiles are generated. For each profile NEWS’s algorithm gives the angular distribution of the scattered field in amplitude and in phase for all geometries and as a function of incident and scattered wave. The acoustic intensity is then treated as a random variable, and histograms are established. The PDF of the scattered intensity is compared to the K, Weibull and lognormal distributions and we examine the statistical informations providing by bistatic sonar.
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