A Method To Simulate Synthetic Aperture Sonar Images With Parameterized Autocorrelation Functions

An approach to simulate synthetic aperture sonar (SAS) images with known autocorrelation functions (ACF) and single-point statistics is presented. ACF models for generating textures with and without periodicities are defined and explained. Simulated textures of these models are compared visually with real SAS image textures. Distortion and degradation of the synthetic textures are examined for various simulation parameter choices.