Modeling the Effect of Seafloor Ripples on Synthetic Aperture Sonar Speckle Statistics

The characterization and modeling of synthetic aperture sonar (SAS) image statistics is of importance for developing target-on-background detection and classification algorithms and for developing specialized filters for speckle noise reduction. In this paper, we present a model to predict the impact of amplitude scaling caused by seafloor ripples on SAS image speckle statistics. The continuous variation in scattering strength produced by ripples (i.e., ripple-induced changes in seafloor slope) is treated as deterministic amplitude scaling on image speckle produced by the SAS imaging process. Changes in image statistics caused by ripples are quantified in terms of an effective -distribution shape parameter. Agreement between shape parameter estimated from the scaling model and from SAS data collected in experiments off Panama City, FL and off the Ligurian coast near La Spezia, Italy illustrate the efficacy of the model.