New HOS-based model for signal detection in non-Gaussian noise: an application to underwater acoustic communications

In the context of digital signal processing addressed to underwater acoustic communications, this work focuses attention on the optimization of detection of weak signals in presence of additive independent stationary non-Gaussian noise. In order to detect signals in the case of low SNR values, the selected binary statistical testing approach consists in a Locally Optimum Detector (LOD), designed on the basis of a new proposed HOS-based model of non-Gaussian noise probability density function (pdf). In particular, an 'asymmetric Gaussian' pdf model is introduced, in order to describe realistically non-Gaussian noise in a very simple way. The resulting test has been compared with the Gaussian-hypothesis LOD test. Experimental results have shown significant advantages in modelling noise pdf on the basis of the proposed pdf function; they derive from the application of the LOD test for detecting known deterministic signals corrupted by real acoustic ship-traffic-radiated noise