Title :
HOS-based noise models for signal detection optimization in non-Gaussian environments
Author :
Tesei, Anna ; Regazzoni, C.S.
Author_Institution :
DIBE, Genoa Univ.
Abstract :
Two probability density function (pdf) models suitable for describing non-Gaussian i.i.d. noise are introduced. The models are used in the design of a locally optimum detector test for detecting weak signals in real non-Gaussian noise. Results obtained in the context of an underwater acoustic application are encouraging
Keywords :
acoustic noise; acoustic signal detection; higher order statistics; optimisation; random noise; signal detection; underwater sound; higher order statistics; locally optimum detector test; noise models; non-Gaussian i.i.d. noise; probability density function models; signal detection optimization; underwater acoustic application; weak signals; Higher order statistics; Signal to noise ratio; Working environment noise;
Conference_Titel :
Information Theory, 1995. Proceedings., 1995 IEEE International Symposium on
Conference_Location :
Whistler, BC
Print_ISBN :
0-7803-2453-6
DOI :
10.1109/ISIT.1995.535811
