Distribution of the Cell Under Test in Sliding Window Detection Processes

Abstract

Analysis of sliding window detection detection processes requires careful consideration of the cell under test, which is an amplitude squared measurement of the signal plus clutter in the complex domain. Some authors have suggested that there is sufficient merit in the approximation of the cell under test by a distributional model similar to that assumed for the clutter distribution. Under such an assumption, the development of Neyman-Pearson detectors is facilitated. The purpose of the current paper is to demonstrate, in a modern maritime surveillance radar context, that such an approximation is invalid.

Interference control in sliding window detection processes using a Bayesian approach

“…Additionally, it will be useful to apply this approach in the context of clutter modelled by Pareto statistics. A useful result, for the relevant density of the target and clutter in the interference cell, can be found in [6].…”