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| Publications [#66606] of Jeffrey L. Krolik
Papers Published
- Tabrikian, Joseph and Krolik, Jeffrey L., 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
(1999),
pp. 1761 - 1764, Phoenix, AZ, USA
(last updated on 2007/04/16)
Abstract: 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.
Keywords: Mathematical models;Markov processes;Backscattering;Radar clutter;
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