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Efficient computation of the Bayesian Cramer-Rao bound on estimating parameters of Markov models

Publication ,  Journal Article
Tabrikian, J; Krolik, JL
Published in: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
January 1, 1999

This paper presents a novel method for calculating the Hybrid Cramer-Rao lower bound (HCRLB) when the statistical model for the data has a Markovian nature. The method applies to both the non-linear/non-Gaussian as well as linear/Gaussian model. The approach solves the required expectation over unknown random parameters by several one-dimensional integrals computed recursively, thus simplifying a computationally-intensive multi- dimensional integration. The method is applied to the problem of refractivity estimation using radar clutter from the sea surface, where the backscatter cross section is assumed to be a Markov process in range. The HCRLB is evaluated and compared to the performance of the corresponding maximum a-posteriori estimator. Simulation results indicate that the HCRLB provides a tight lower bound in this application.

Duke Scholars

Published In

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

ISSN

0736-7791

Publication Date

January 1, 1999

Volume

3

Start / End Page

1761 / 1764
 

Citation

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Tabrikian, J., & Krolik, J. L. (1999). Efficient computation of the Bayesian Cramer-Rao bound on estimating parameters of Markov models. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 3, 1761–1764.
Tabrikian, J., and J. L. Krolik. “Efficient computation of the Bayesian Cramer-Rao bound on estimating parameters of Markov models.” ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings 3 (January 1, 1999): 1761–64.
Tabrikian J, Krolik JL. Efficient computation of the Bayesian Cramer-Rao bound on estimating parameters of Markov models. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. 1999 Jan 1;3:1761–4.
Tabrikian, J., and J. L. Krolik. “Efficient computation of the Bayesian Cramer-Rao bound on estimating parameters of Markov models.” ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 3, Jan. 1999, pp. 1761–64.
Tabrikian J, Krolik JL. Efficient computation of the Bayesian Cramer-Rao bound on estimating parameters of Markov models. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. 1999 Jan 1;3:1761–1764.

Published In

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

ISSN

0736-7791

Publication Date

January 1, 1999

Volume

3

Start / End Page

1761 / 1764