HOS-based modelling of low-frequency underwater acoustic noise for signal detection in shallow waters

This paper aims to provide realistic modelling of generic noise probability density functions (pdfs). The target is to obtain a parametric model depending on few parameters, and being so general to be able to describe many kinds of noise (e.g., symmetric or asymmetric, with variable sharpness). A very general and easy-to-use function which is based on HOS parameters is presented and compared with other HOS-based pdfs; it is called asymmetric generalized Gaussian. A real case study is considered for comparing the various pdfs; it consists in modelling real underwater acoustic noise at low frequencies and applying the estimated models to designed locally optimum detection (LOD) tests.

[1]  S. Kassam Signal Detection in Non-Gaussian Noise , 1987 .

[2]  Hagit Messer,et al.  Suboptimal detection of non-Gaussian signals by third-order spectral analysis , 1990, IEEE Trans. Acoust. Speech Signal Process..

[3]  R. Dwyer Use of the kurtosis statistic in the frequency domain as an aid in detecting random signals , 1984 .

[4]  Gary R. Wilson,et al.  Detection of non-Gaussian signals in non-Gaussian noise using the bispectrum , 1990, IEEE Trans. Acoust. Speech Signal Process..

[5]  C. L. Nikias,et al.  Signal processing with alpha-stable distributions and applications , 1995 .

[6]  Alessandra Tesei,et al.  Use of fourth-order statistics for non-Gaussian noise modelling: The generalized Gaussian pdf in terms of kurtosis , 1996, 1996 8th European Signal Processing Conference (EUSIPCO 1996).

[7]  Carlo S. Regazzoni,et al.  The asymmetric generalized Gaussian function: a new HOS-based model for generic noise pdfs , 1996, Proceedings of 8th Workshop on Statistical Signal and Array Processing.

[8]  John B. Thomas,et al.  Detectors for discrete-time signals in non-Gaussian noise , 1972, IEEE Trans. Inf. Theory.

[9]  Carlo S. Regazzoni,et al.  A new HOS-based model for signal detection in non-Gaussian noise: an application to underwater acoustic communications , 1995, 'Challenges of Our Changing Global Environment'. Conference Proceedings. OCEANS '95 MTS/IEEE.

[10]  R. Webster Ambient noise statistics , 1993, IEEE Trans. Signal Process..

[11]  Georgios B. Giannakis,et al.  Signal detection and classification using matched filtering and higher order statistics , 1989, IEEE Trans. Acoust. Speech Signal Process..

[12]  A. Bruce Carlson,et al.  Communication Systems , 1968 .

[13]  Ian F. Blake,et al.  Detection in multivariate non-Gaussian noise , 1994, IEEE Trans. Commun..

[14]  C. L. Nikias,et al.  Signal processing with higher-order spectra , 1993, IEEE Signal Processing Magazine.