The weighted curvature approximation in scattering from sea surfaces

Type Article
Date 2010
Language English
Author(s) Guerin Charles-Antoine1, Soriano Gabriel2, Chapron Bertrand3
Affiliation(s) 1 : Univ Sud Toulon Var, LSEET, CNRS, La Garde, France.
2 : Univ Paul Cezanne, Inst Fresnel, CNRS, Marseille, France.
3 : IFREMER, Lab Oceanog Spatiale, Plouzane, France.
Source Waves In Random And Complex Media (1745-5030) (Taylor & Francis Ltd), 2010 , Vol. 20 , N. 3 , P. 364-384
DOI 10.1080/17455030903563824
WOS© Times Cited 30
Abstract A family of unified models in scattering from rough surfaces is based on local corrections of the tangent plane approximation through higher-order derivatives of the surface. We revisit these methods in a common framework when the correction is limited to the curvature, that is essentially the second-order derivative. The resulting expression is formally identical to the weighted curvature approximation, with several admissible kernels, however. For sea surfaces under the Gaussian assumption, we show that the weighted curvature approximation reduces to a universal and simple expression for the off-specular normalized radar cross-section ( NRCS), regardless of the chosen kernel. The formula involves merely the sum of the NRCS in the classical Kirchhoff approximation and the NRCS in the small perturbation method, except that the Bragg kernel in the latter has to be replaced by the difference of a Bragg and a Kirchhoff kernel. This result is consistently compared with the resonant curvature approximation. Some numerical comparisons with the method of moments and other classical approximate methods are performed at various bands and sea states. For the copolarized components, the weighted curvature approximation is found numerically very close to the cut-off invariant two-scale model, while bringing substantial improvement to both the Kirchhoff and small-slope approximation. However, the model is unable to predict cross-polarization in the plane of incidence. The simplicity of the formulation opens new perspectives in sea state inversion from remote sensing data.
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