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Fast wideband source separation based on higher-order statistics

S. Bourennane 1 M. Frikel 2, 3 A. Bendjama 1
1 FRESNEL - Institut FRESNEL
2 LAC - Laboratoire d'automatique de Caen
3 GREYC - Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen
Abstract : In this paper we develop an algorithm to improve the accuracy of the estimation of the direction of arrival of the wide-band sources. It is well known that when the noise cross-spectral matrix is unknown, these estimates may be grossly inaccurate. Using both the fourth order cumulant for suppression of the Gaussian noise, the transformation matrices for estimating the coherent signal subspace and a noneigenvector algorithm a robust method for the source characterisation problem in the presence of noise with an unknown cross-spectral matrix is developed. We show that the performance of bearing estimation algorithms improves substantially when our robust algorithm is used. Simulation results are presented for the unknown noise spectral matrix.
Keywords : Wideband Source separation Higher order statistics Signal processing algorithms Direction of arrival estimation Gaussian noise Covariance matrix Noise measurement Noise robustness Background noise
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Conference papers
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https://hal-normandie-univ.archives-ouvertes.fr/hal-01821508
Contributor : Miloud Frikel <>
Submitted on : Friday, June 22, 2018 - 2:58:52 PM
Last modification on : Thursday, April 1, 2021 - 4:12:46 PM

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COMUE-NORMANDIE | CNRS | EC-MARSEILLE | ENSICAEN | UNIV-AMU | GREYC | UNICAEN | LAC | LAC-IDO | IF

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S. Bourennane, M. Frikel, A. Bendjama. Fast wideband source separation based on higher-order statistics. IEEE Signal Processing Workshop on Higher-Order Statistics, Jul 1997, Banff, Canada. ⟨10.1109/HOST.1997.613546⟩. ⟨hal-01821508⟩

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