Name
Title | ||
|---|---|---|
First- and Second-Order Moments of the Normalized Sample Covariance Matrix of Spherically Invariant Random Vectors |
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 |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/LSP.2006.888400 | Signal Processing Letters, IEEE |
Keywords | Field | DocType |
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,Estimation,normalized sample covariance matrix (NSCM),performance analysis,spherically invariant random vectors (SIRV) | Mathematical optimization,Covariance function,Estimation of covariance matrices,Law of total covariance,Covariance intersection,Invariant (mathematics),Gaussian process,Covariance mapping,Mathematics,Covariance | Journal |
Volume | Issue | ISSN |
14 | 6 | 1070-9908 |
Citations | PageRank | References |
8 | 0.79 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bausson, S. | 1 | 8 | 0.79 |
| Frédéric Pascal | 2 | 128 | 16.30 |
| P. Forster | 3 | 187 | 16.94 |
| Jean Philippe Ovarlez | 4 | 190 | 25.11 |