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利用多传感器的信息融合进行目标识别,可以避免单一传感器的局限性,减少各传感器不确定性的影响.本文描述了一个用于目标识别与分类的基于模型的多传感器系统,该系统选用以决策层为主的方法,以模糊神经网络作为其信息融合的工具.通过比较基于融合信息进行分类的结果与单传感器分类的结果,说明了多传感器信息融合的优越性.
Using multi-sensor information fusion to identify target can avoid the limitation of single sensor and reduce the influence of each sensor’s uncertainty.This paper describes a model-based multi-sensor system for target identification and classification, which is used to make decision Layer based approach to fuzzy information fusion as a tool for information fusion.Through comparing the results of the classification based on the fusion information and the single sensor classification, the superiority of multi-sensor information fusion is illustrated.