引用本文: | 李宏,徐晖,安玮,等.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.[点击复制] |
Li Hong,Xu Hui,An Wei,et al.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[点击复制] |
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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 |
李宏, 徐晖, 安玮, 孙仲康 |
(国防科技大学 电子工程学院 湖南 长沙 410073)
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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 |
DOI: |
投稿日期:1996-10-07 |
基金项目:国家自然科学基金资助项目 |
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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, Sun Zhongkang |
(Institute of Electronic Engineering, NUDT, Changsha, 410073)
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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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