Locally Optimum Detection of Random Signals

Abstract

Listen

Translate article

Although the problem of finding good detection schemes for signals buried in noise processes has been considered in various situations, much of such work has concentrated mainly on detection of known signals with or without a finite number of random parameters. Less attention has been paid to the problem of detecting random (stochastic) signals, although there does exist a reasonable literature on this subject. (Again, we will use the terms ’random signal’ and ’stochastic signal’ interchangeably in this book.) Random signals are of practical interest in a number of situations. For example, in underwater applications it is often impossible to represent desired signals by known or parametric models because of random dispersion resulting from turbulence and inhomogeneities in the propagation medium, and also often because of the very nature of the signal source.KeywordsNoise ModelMultiplicative NoiseRandom SignalArray SizeOptimum DetectorThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.