基于Choquet模糊积分的决策层信息融合目标识别
Decision-level information fusion for target recognition based on choquet fuzzy integral
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摘要: 引入模糊测度和 Choquet模糊积分的概念后,信息融合目标识别可转化为各信源识别结果关于信源重要程度的广义 Lebesgue积分。该文给出了 Choquet模糊积分应用于决策层信息融合目标识别的通用技术路线,并提供了信源重要程度的度量方法。算法实用于红外/毫米波融合目标识别系统,融合识别结果与 D-S 证据理论方法作了比较,证明了基于 Choquet模糊积分方法的有效性。Abstract: After introducing the concept of fuzzy measures and Choquet fuzzy integral, infor-mation fusion for target recognition can turn into generalized Lebesgue integral of recognition result with respect to the degree of importance of source. This paper presents a generalized recognition flow in decision-level information fusion based on Choquet fuzzy integral, and pro-vides a method for measuring the degree of importance of source. The algorithm is proved in the real IR/MMW fusion recognition system, the fusion result of recognition which compares with that of D-S evidence theory shows the efficiency of the method based on Choquet fuzzy integral.
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