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基于BP 网络与D-S理论相结合的点目标状态下卫星及其伴飞诱饵的识别方法
引用本文:李宏,徐晖,安玮,孙仲康.基于BP 网络与D-S理论相结合的点目标状态下卫星及其伴飞诱饵的识别方法[J].国防科技大学学报,1997,19(2):53-58.
作者姓名:李宏  徐晖  安玮  孙仲康
作者单位:国防科技大学电子工程学院
摘    要:本文提出的点目标状态下卫星及其伴飞锈饵的识别方法是基于BP网络与D-S理论相结合的信息融合方法。该方法采用目标的红外辐射特征,先用BP网络对目标进行粗分类,然后用D-S理论对BP网络的多次识别结果进行融合。仿真实验结果表明,D-S理论的最后输出比BP网络的输出识别率得到很大的改善,抗噪能力得到很大的提高

关 键 词:神经网络,证据理论,点目标,模式识别
收稿时间:1996/10/7 0:00:00

A Method Based on the Combination of BP Networks and D-S Theory to Recognize Satellite and its Companion Decoy in the State of Point Target
Li Hong,Xu Hui,An Wei and Sun Zhongkang.A Method Based on the Combination of BP Networks and D-S Theory to Recognize Satellite and its Companion Decoy in the State of Point Target[J].Journal of National University of Defense Technology,1997,19(2):53-58.
Authors:Li Hong  Xu Hui  An Wei and Sun Zhongkang
Institution:Institute of Electronic Engineering, NUDT, Changsha, 410073;Institute of Electronic Engineering, NUDT, Changsha, 410073;Institute of Electronic Engineering, NUDT, Changsha, 410073;Institute of Electronic Engineering, NUDT, Changsha, 410073
Abstract:An information fusion method based on the combination of BP neural networks and D S evidence theory to recognize satellite and its companion decoy in the state of point target is proposed in the paper.A BP networks is adopted to recognize the patterns with the characteristics of infrared(IR)radiation at first, then the D S evidence theory is used to fuse the results derived from the BP networks at different time. The result of emulatson shows that the true rate of D S is much higher than BP,and the ability to reject disturbance and noise is raised very much.
Keywords:neural networks  evidence theory  point target  pattern recognition    
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