Cramer-Rao bound on the estimation accuracy of complex-valued homogeneous Gaussian random fields
This paper considers the problem of the achievable accuracy in jointly estimating the parameters of a complex-valued two-dimensional (2-D) Gaussian and homogeneous random field from a single observed realization of it. Based on the 2-D Wold decomposition, the field is modeled as a sum of purely inde...
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Veröffentlicht in: | IEEE transactions on signal processing 2002-03, Vol.50 (3), p.710-724 |
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Sprache: | eng |
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Zusammenfassung: | This paper considers the problem of the achievable accuracy in jointly estimating the parameters of a complex-valued two-dimensional (2-D) Gaussian and homogeneous random field from a single observed realization of it. Based on the 2-D Wold decomposition, the field is modeled as a sum of purely indeterministic, evanescent, and harmonic components. Using this parametric model, we first solve a key problem common to many open problems in parametric estimation of homogeneous random fields: that of expressing the field mean and covariance functions in terms of the model parameters. Employing the parametric representation of the observed field mean and covariance, we derive a closed-form expression for the Fisher information matrix (FIM) of complex-valued homogeneous Gaussian random fields with mixed spectral distribution. Consequently, the Cramer-Rao lower bound on the error variance in jointly estimating the model parameters is evaluated. |
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ISSN: | 1053-587X 1941-0476 |
DOI: | 10.1109/78.984769 |