On the Fisher Information Matrix for Multivariate Elliptically Contoured Distributions

The Slepian-Bangs formula provides a very convenient way to compute the Fisher information matrix (FIM) for Gaussian distributed data. The aim of this letter is to extend it to a larger family of distributions, namely elliptically contoured (EC) distributions. More precisely, we derive a closed-form expression of the FIM in this case. This new expression involves the usual term of the Gaussian FIM plus some corrective factors that depend only on the expectations of some functions of the so-called modular variate. Hence, for most distributions in the EC family, derivation of the FIM from its Gaussian counterpart involves slight additional derivations. We show that the new formula reduces to the Slepian-Bangs formula in the Gaussian case and we provide an illustrative example with Student distributions on how it can be used.

[1]  Marco Lops,et al.  Asymptotically optimum radar detection in compound-Gaussian clutter , 1995 .

[2]  S. Kay Fundamentals of statistical signal processing: estimation theory , 1993 .

[3]  Yuri I. Abramovich,et al.  Diagonally Loaded Normalised Sample Matrix Inversion (LNSMI) for Outlier-Resistant Adaptive Filtering , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[4]  Alfred O. Hero,et al.  Robust Shrinkage Estimation of High-Dimensional Covariance Matrices , 2010, IEEE Transactions on Signal Processing.

[5]  Fang Kaitai,et al.  Relationships among classes of spherical matrix distributions , 1984 .

[6]  P. Krishnaiah,et al.  Complex elliptically symmetric distributions , 1986 .

[7]  Fulvio Gini,et al.  Covariance matrix estimation for CFAR detection in correlated heavy tailed clutter , 2002, Signal Process..

[8]  Brian M. Sadler,et al.  Performance analysis for direction finding in non-Gaussian noise , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[9]  C. Richmond A note on non-Gaussian adaptive array detection and signal parameter estimation , 1996, IEEE Signal Processing Letters.

[10]  David E. Tyler Statistical analysis for the angular central Gaussian distribution on the sphere , 1987 .

[11]  David E. Tyler,et al.  Redescending $M$-Estimates of Multivariate Location and Scatter , 1991 .

[12]  E. J. Kelly An Adaptive Detection Algorithm , 1986, IEEE Transactions on Aerospace and Electronic Systems.

[13]  Christ D. Richmond,et al.  Adaptive array signal processing and performance analysis in non-Gaussian environments , 1996 .

[14]  Ananthram Swami,et al.  Cramer-Rao bounds for deterministic signals in additive and multiplicative noise , 1996, Signal Process..

[15]  E. Conte,et al.  Characterization of radar clutter as a spherically invariant random process , 1987 .

[16]  K. Fang,et al.  Generalized Multivariate Analysis , 1990 .

[17]  Kai-Tai Fang,et al.  Theory and Applications of Elliptically Contoured and Related Distributions , 1990 .

[18]  H. Vincent Poor,et al.  Complex Elliptically Symmetric Distributions: Survey, New Results and Applications , 2012, IEEE Transactions on Signal Processing.

[19]  David S. Slepian,et al.  Estimation of signal parameters in the presence of noise , 1954, Trans. IRE Prof. Group Inf. Theory.

[20]  Ami Wiesel,et al.  Unified Framework to Regularized Covariance Estimation in Scaled Gaussian Models , 2012, IEEE Transactions on Signal Processing.

[21]  David E. Tyler,et al.  Maximum likelihood estimation for the wrapped Cauchy distribution , 1988 .

[22]  Kung Yao,et al.  A representation theorem and its applications to spherically-invariant random processes , 1973, IEEE Trans. Inf. Theory.

[23]  Philippe Forster,et al.  Covariance Structure Maximum-Likelihood Estimates in Compound Gaussian Noise: Existence and Algorithm Analysis , 2008, IEEE Transactions on Signal Processing.

[24]  Athanasios C. Micheas,et al.  Complex elliptical distributions with application to shape analysis , 2006 .

[25]  David E. Tyler A Distribution-Free $M$-Estimator of Multivariate Scatter , 1987 .