Articolo in rivista, 2002, ENG, 10.1016/S0165-1684(02)00319-5

Time-frequency based detection in impulsive noise environments using alpha-stable noise models

Coates M.J.; Kuruoglu E.E.

Department of Electrical and Computer Engineering, McGill University, Montreal, Quebec, Canada; CNR-ISTI, Pisa, Italy

We develop near-optimal test statistics for the detection of arbitrary non-stationary second-order random signals in impulsive noise, modelled using a bivariate, isotropic ?-stable distribution. The test statistics are derived by approximating the noise model using a mixture of Gaussians, trained using an expectation-maximisation algorithm. We consider the extension to the case when the signal to be detected is subjected to an unknown time-frequency or time-scale shift, and show that approximations to locally optimal test statistics can be implemented using bilinear time-frequency or time-scale representations. We demonstrate that the performance of the locally optimal linear receiver is poor in even mildly impulsive noise; the alternative detection statistics proposed in this paper offer considerably enhanced performance.

Signal processing (Print) 82 (12), pp. 1917–1925

Keywords

Alpha-stable noise, Time-frequency analysis, Detection

CNR authors

Kuruoglu Ercan Engin

CNR institutes

ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"

ID: 43676

Year: 2002

Type: Articolo in rivista

Creation: 2009-06-16 00:00:00.000

Last update: 2017-11-07 17:12:40.000

External IDs

CNR OAI-PMH: oai:it.cnr:prodotti:43676

DOI: 10.1016/S0165-1684(02)00319-5

ISI Web of Science (WOS): 000179200800008

Scopus: 2-s2.0-0036887828