Clutter model for VHF SAR imagery

We present a physically-based clutter model for low frequency synthetic aperture radar that includes both distributed scatterers and large-amplitude discrete clutter. The model is used to generate a synthetic forest clutter scene comprised of two components, a background component and a heavy-tailed discrete component. Model parameters are based on characteristics of the scene, such as the radar cross-section of trees, forest thickness, and background radar cross-section. A synthetic SAR image of the scene is generated by modelling the radar imaging process as a lowpass filter and convolving the scene with the impulse response of the radar. We compare the synthetic, single-pass clutter image to measured data and present a metric for evaluating model fit. We also extended the model to describe correlated, multi-pass images for change detection applications.