Ocean Wind Waves Surface Roughness Modeling and SAR Clutter Characterization Under Varying Sea States Using Inverese Backscattering Method

This paper addresses traditional limitations in clutter estimation of ocean surfaces that inadequately capture roughness details from both short and long wind waves by proposing a numerical approach in which wave heights are modeled by sea states. The model integrates contributions from both long and short ocean waves using a composite ocean wave scattering (OWS) formulation, alongside various spreading functions such as half-cosine, parameterized half-cosine, hyperbolic secant-squared, and two-scale types, to reconstruct the 3D ocean surface. Moreover, it examines the directional distributions of waves and computes corresponding wave height profiles in response to dynamic, inherently time-varying sea states. These models, especially the roughness profile, are subsequently integrated into an inverse scattering method for SAR electromagnetic interaction analysis, enabling the generation of SAR volume backscattering profiles. While the modeling offers valuable insights into ocean surface clutter, the inherent limitations in the OWS formulations and numerical approximations, resulting from experimental constraints, suggest that no single ocean model consistently outperforms the others. Furthermore, all objective quality assessments confirm that the results align with the underlying theories.