Estimation of Large Toeplitz Covariance Matrices and Application to Source Detection

Abstract : In this paper, performance results of two types of Toeplitz covariance matrix estimators are provided. Concentration inequalities for the spectral norm for both estimators have been derived showing exponential convergence of the error to zero. It is shown that the same rates of convergence are obtained in the case where the aggregated matrix of time samples is corrupted by a rank one matrix. As an application based on this model, source detection by a large dimensional sensor array with temporally correlated noise is studied.
Type de document :
Communication dans un congrès
EUSIPCO'14, Sep 2014, Lisbon, Portugal. Proceedings of the 22nd European Signal Processing Conference, pp.2120 - 2124
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https://hal-supelec.archives-ouvertes.fr/hal-01092899
Contributeur : Catherine Magnet <>
Soumis le : mardi 9 décembre 2014 - 16:39:43
Dernière modification le : jeudi 29 mars 2018 - 11:06:05

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  • HAL Id : hal-01092899, version 1

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J. Vinogradova, Romain Couillet, Walid Hachem. Estimation of Large Toeplitz Covariance Matrices and Application to Source Detection. EUSIPCO'14, Sep 2014, Lisbon, Portugal. Proceedings of the 22nd European Signal Processing Conference, pp.2120 - 2124. 〈hal-01092899〉

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