General Mathematics

    

DSmH Evidential Network for Target Identication

Authors: Xian LI, Zhigang CHEN, Peiliang JING

This paper proposes a model of evidential network based on Hybrid Dezert-Smarandache theory (DSmH) to improve target identication of multi-sensors. In the classication simulation, we compared the results obtained at the Target Type node and Foe-Ally node in evidential network by using Dempster-Shafer theory (DS) and using DSmH. The comparisons show that, when we use DSmH in the evidential network, we can assign more Basic Belief Assignments (BBA) to the focal element the target belongs to. Experiments conrm that the model of evidential network using DSmH is better than the one using DS.

Comments: 8 Pages.

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Submission history

[v1] 2015-08-31 03:11:17

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