Signal Detection and Normalization in Underwater Noises Modeled as a Gaussian-Gaussian Mixture 7. AUTMORf*;
نویسندگان
چکیده
Knowledge of the noise probability density function (PDF) is central in signal detection problems, not only for optimum receiver structures but also for processing procedures such as power normalization. Unfortunately, the statistical knowledge must be acquired since the classical assumption of a Gaussian noise PDF is often not valid in underwater acoustics. In this report, we study statistical modeling by a GaussianGaussian mixture for three different underwater noise samples. We show that one of them can adequately be described by a Gaussian-Gaussian mixture, one is very close to a Gaussian model and is described by a mixture with a very small perturbating term, whereas the third one seems closer to the Middleton class A model but is non-stationary. * On leave from Groupe d'Etude et de Recherche en Detection Sous-Marine, Le Brusc, 83140 SIX-FOURS LES PLAGES (FRANCE). Key-words: non-Gaussian detection, adaptive normalization, noise model, underwater noises.
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