Neyman-Pearson Optimal and Suboptimal Detection for Signals in General Clutter Mixture Distributions

摘要

A general framework is introduced that enables the construction of the Neyman-Pearson optimal detector for a single general target model embedded within complex clutter whose amplitude distribution forms a mixture. This enables the determination of asymptotic decision rules for high resolution high grazing angle detection of targets in spiky sea clutter. In addition, suboptimal approximations are derived and analysed.