Abstract
A practical technique for characterizing non-Gaussian radar clutter is specified and demonstrated using Over The Horizon Radar (OTHR) data, as an example. The technique employs maximum likelihood to fit the probability density of the clutter amplitude returns to a mixture of two Rayleigh probability densities instead of the single Rayleigh density typically used for Gaussian clutter. This model for non-Gaussian clutter is fully specified for any set of clutter amplitudes by a log likelihood, two Rayleigh parameters, and a mixing coefficient. A 3D plot of these values yields an easily-visualized clutter characterization, as is illustrated using OTHR data. This technique is a demonstration of clutter characterization using OTHR data, but the method can be applied to characterize other types of clutter data.
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