基于模糊神经网络和D-S推理的智能特征信息融合研究

INVESTIGATION ON INTELLIGENT ATTRIBUTE INFORMATION FUSION BASED ON FUZZY NEURAL NETWORK AND D-S INFERENCE

  • 摘要: 给出了一种新的分布式多传感器智能特征信息融合系统结构,利用模糊神经网络技术把环境信息和专家语言信息引入融合系统,提出了一种新的智能特征信息融合算法.同时,利用红外、雷达、敌我识别器等多传感器信息对自动目标识别问题进行了仿真研究.结果表明,新的智能融合算法能较大程度地提高运算速度,并具有较强的抗环境干扰能力和较高的融合系统可靠性.

     

    Abstract: In this paper,a new structure of distributed multi-sensor intelligent attribute fusion system is given. By use of fuzzy neural network ,the environmental-and-expert verbal information is introduced into the fusion system and a new intelligent attribute information fusion algorithm is presented. An example of automatic target recognition fis given by use of the information from IFFN ,IRST and RADAR.The simulation shows that the new algorithm can speed calculation greatly,and the system has better ability of resisting the environmental disturbance and higher system reliabilily.

     

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