Recent research has shown that the Pareto family of distributions provides suitable intensity models for high resolution X-band maritime surveillance radar clutter. In particular, the two parameter Pareto Type II model has been shown to fit the Australian Defence Science and Technology Group's medium to high grazing angle clutter returns very well. The Pareto Type II model is a special case of a Burr distributional model, which is a three parameter power law statistical model. Hence this paper begins by investigating the fitting of the Burr model to real data. Based upon these results a detailed study of the development of non-coherent sliding window detectors is justified, for operation in such clutter. Several different approaches will be applied to construct the decision rules. These include a transformation approach and direct adaptation of such detectors, designed for operation in exponentially distributed clutter, to the Burr clutter setting. In addition to this, the fact that the Burr distribution is invariant with respect to two of its distributional parameters allows specication of detection processes which have the constant false alarm rate property with respect to these model parameters. Performance analysis, in simulated clutter, of the derived detectors is then examined. This includes performance in the presence of interference and false alarm regulation during clutter power transitions. This is complemented by an application of the decision rules to target detection in real high resolution X-band maritime surveillance radar clutter.
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