Stochastic fusion of heterogeneous multisensor information for robust data-to-decision

In this paper, based on the measure-theoretic probability theory and the theory of stochastic differential equation (SDE), a stochastic fusion framework is proposed for the heterogeneous sensor network for the purpose of robust decision making. In this framework, for each sensor, its sample space an...

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Bibliographic Details
Published inProceedings of the 16th International Conference on Information Fusion pp. 2185 - 2191
Main Authors Xin Chen, Jousselme, Anne-Laure, Valin, Pierre, Kirubarajan, T.
Format Conference Proceeding
LanguageEnglish
Published ISIF ( Intl Society of Information Fusi 01.07.2013
Subjects
Bayesian decision
Decision making
hard/soft fusion
heterogeneous sensor network
Random processes
Random variables
robust
Robustness
Target tracking
Uncertainty
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Summary:In this paper, based on the measure-theoretic probability theory and the theory of stochastic differential equation (SDE), a stochastic fusion framework is proposed for the heterogeneous sensor network for the purpose of robust decision making. In this framework, for each sensor, its sample space and the corresponding σ-algebra are defined. Then, random variables, which are designed to meet the requirements of the operation in the battle field, are defined over the pairs of sample space and its σ-algebra. After that, the conditional expectation is taken for those random variables conditional on the union of σ-algebras to finish the information fusion process. Furthermore, to make the decision making process more robust, the undesired uncertainty in the fused information is hedged out based on the theory of SDEs, before the fused information is used for the decision making.
ISBN:9786058631113
6058631114