Minimax Robust Optimal Estimation Fusion for Distributed Multisensor Systems with a Relative Entropy Uncertainty

Hua Li and Jie Zhou

Mathematical Problems in Engineering, 2014, vol. 2014, 1-6

Abstract:

This paper considers the robust estimation fusion problem for distributed multisensor systems with uncertain correlations of local estimation errors. For an uncertain class characterized by the Kullback-Leibler (KL) divergence from the actual model to nominal model of local estimation error covariance, the robust estimation fusion problem is formulated to find a linear minimum variance unbiased estimator for the least favorable model. It is proved that the optimal fuser under nominal correlation model is robust while the estimation error has a relative entropy uncertainty.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:910971

DOI: 10.1155/2014/910971

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