Inverse scattering with far-field intensity data

The rough surface inverse scattering problem is studied using evolutionary strategies. The objective is to reconstruct the surface profile function from far-field angle-resolved scattered intensity data. For simplicity, the random surface is assumed to be one-dimensional and perfectly conducting. The optimum of the fitness function is searched using two versions of the evolutionary strategies; the non-elitist (mu, lambda) strategy, and the elitist (mu + lambda) strategy. The search space is reduced with the assumption that the unknown surface profile constitutes a realization of a stationary zero-mean Gaussian random process with a Gaussian correlation function With the conditions and parameters employed, the surface profile can be retrieved with high degree of confidence. Issues related to the lack of uniqueness of the solution are also discussed.