Detection Performance of Generalized Likelihood Ratio Processors for RandomSignals of Unknown Location, Structure, Extent, and Strength

摘要

A signal (if present) is located somewhere in a band of frequencies characterizedby a total of N search bins. The signal occupies an arbitrary set of M of these bins, where not only is M unknown, but also, the locations of the particular M occupied bins are unknown. Also, the signal strength is unknown. The generalized likelihood ratio (GLR) method furnishes an approach for estimating all the unknown parameters and for testing for presence or absence of the signal in an observation of the outputs of the N search bins. However, there is nothing guaranteed optimum about the GLR approach. Also, the optimum (likelihood ratio) processor cannot be constructed or realized, due to all the unknowns and the voluminous amount of searching required for this scenario. These deleterious conditions force adoption of some suboptimum processing techniques, guided by the GLR and likelihood ratio results. Detection, Likelihood ratio, Generalized Likelihood, Unknown Location, Unknown structure, Unknown Extent, Unknown strength, Maximum likelihood, False alarm probability, Detection probability, Order statistics, Characteristic function, Simulation.