This chapter begins the investigation of sliding window detection processes for clutter modelled by a Pareto Type I distribution. Detector performance begins with the homogeneous clutter case, and with clutter simulated from a Pareto Type I distribution whose shape and scale parameters are matched to Ingara data set run 34683. The performance of the detectors becomes much more interesting when independent interfering targets are inserted into the clutter range profile. These can occur, in a sliding window detection process, for a number of reasons. The first is that the target in the Cell under test (CUT) may be range spread, resulting in target power spillover into adjacent clutter range cells. The chapter examines the direct adaptation of constant false alarm rate (CFAR) detectors from the exponential distributed clutter case to the Pareto scenario. It shows that the CFAR property could not be attained with respect to the Pareto shape parameter, but certainly could be achieved with respect to the Pareto scale parameter.