期刊
IEEE SIGNAL PROCESSING LETTERS
卷 28, 期 -, 页码 2092-2096出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LSP.2021.3117443
关键词
Covariance matrices; Random variables; Gaussian distribution; Symmetric matrices; Reactive power; Radar signal processing; Maximum likelihood estimation; Sample covariance matrix; sample variation; mean squared error; complex Gaussian distribution; complex elliptically symmetric distribution
资金
- National Science Foundation [DMS-1812198]
In this study, we investigate the variance-covariance matrix of affine equivariant matrix-valued statistics when sampling from complex elliptical distributions, and derive the variance-covariance matrix of the sample covariance matrix (SCM) along with its theoretical mean squared error (MSE) when finite fourth-order moments exist. Illustrative examples of the formulas are also provided.
We derive the form of the variance-covariance matrix for any affine equivariant matrix-valued statistics when sampling from complex elliptical distributions. We then use this result to derive the variance-covariance matrix of the sample covariance matrix (SCM) as well as its theoretical mean squared error (MSE) when finite fourth-order moments exist. Finally, illustrative examples of the formulas are presented.
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