DocumentCode :
857716
Title :
First- and Second-Order Moments of the Normalized Sample Covariance Matrix of Spherically Invariant Random Vectors
Author :
Bausson, Sébastien ; Pascal, Frédéric ; Forster, Philippe ; Ovarlez, Jean-Philippe ; Larzabal, Pascal
Author_Institution :
Groupe d´´Electromagnetisme Applique, Univ. Paris X, Ville D´´Avray
Volume :
14
Issue :
6
fYear :
2007
fDate :
6/1/2007 12:00:00 AM
Firstpage :
425
Lastpage :
428
Abstract :
Under Gaussian assumptions, the sample covariance matrix (SCM) is encountered in many covariance based processing algorithms. In case of impulsive noise, this estimate is no more appropriate. This is the reason why when the noise is modeled by spherically invariant random vectors (SIRV), a natural extension of the SCM is extensively used in the literature: the well-known normalized sample covariance matrix (NSCM), which estimates the covariance of SIRV. Indeed, this estimate gets rid of a fluctuating noise power and is widely used in radar applications. The aim of this paper is to derive closed-form expressions of the first- and second-order moments of the NSCM
Keywords :
Gaussian processes; covariance matrices; impulse noise; radar signal processing; signal sampling; Gaussian assumption; NSCM; SIRV; closed-form expression; first-order moments; impulsive noise; normalized sample covariance matrix; radar application; second-order moments; spherically invariant random vectors; Closed-form solution; Clutter; Covariance matrix; Eigenvalues and eigenfunctions; Fading; Matrix decomposition; Maximum likelihood estimation; Performance analysis; Radar applications; Sonar; Estimation; normalized sample covariance matrix (NSCM); performance analysis; spherically invariant random vectors (SIRV);
fLanguage :
English
Journal_Title :
Signal Processing Letters, IEEE
Publisher :
ieee
ISSN :
1070-9908
Type :
jour
DOI :
10.1109/LSP.2006.888400
Filename :
4202611
Link To Document :
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