This chapter introduces a transformation approach for detector design, where the sliding window constant false alarm rate (CFAR) detectors for exponential intensity clutter models are adapted for use in any clutter environment of interest. The key to the transformation approach is exploitation of, which allow one to begin with the exponential-based CFAR detectors Pfa expression, and then transform it to an expression involving the desired clutter model. With reference to the Pareto Type I and II distributions it follows that unless the clutter is modelled by a one parameter model it will not be possible to produce a fully CFAR decision rule via the transformation approach alone. The validity of a single parameter Pareto-type distribution, as a model for X-band maritime surveillance radar clutter, is now investigated. Although the results discount the suitability of the one-parameter Lomax model for X-band maritime surveillance radar clutter, one can still explore detection performance under such a clutter model assumption.