Generating non-Gaussian random fields for sea surface simulations

Sea surface simulations are needed to generate realistic glitter in Monte-Carlo testing of automatic target detection in electro-optical imagery of sea scenes. Glitter is determined by the sea surface's height and slope. At present sea surfaces are generally modelled as correlated random fields. Current algorithms for generating large realizations of random fields generally produce correlated Gaussian fields, but the available empirical statistics on sea surfaces show a non-Gaussian distribution of point slope values. The paper introduces a class of non-Gaussian random fields with specified correlation functions and point distributions of slopes generated by pointwise transformation of Gaussian fields. This definition allows generation of large scale simulations of such fields through simple pointwise transformation of simulations of the associated Gaussians.<
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