神经网络在光电干扰效能预测中的应用  

Application of Neural Network in Forecast of Photoelectric Jamming Effect

作　　者：郭豹[1] 李忠华[1] 杨寿佳[1] 张兵[1] 

机构地区：[1]中国电子科技集团公司第二十七研究所,郑州450047

出　　处：《电光与控制》2015年第9期60-63,共4页Electronics Optics & Control

摘　　要：介绍了闭环光电对抗的发展现状。为了实现干扰效能的预测评估,通过分析激光干扰导引设备的原理及影响因素,采用BP神经网络方法建立了干扰效能预测模型,并进行了干扰试验。经过预测结果和试验结果的对比分析,验证了预测模型的准确性,为该方法在闭环光电对抗中的可行性分析提供了一定的应用研究基础。The development status of closed-loop electro-optic countermeasure technology was introduced. In order to obtain the forecast evaluation of photoelectric jamming effectiveness, a forecast evaluation model was built up based on BP neural network by analyzing the technical principle and influence factors of laser jamming to optical seeker, and some photoelectric jamming experiments were implemented. After the comparative analysis to forecast result and experiment result, the accuracy of the prediction model was verified. The research can provide an application foundation for feasibility analysis of this method in photoelectric countermeasure.

关 键 词：光电干扰 神经网络 预测模型 

分 类 号：O436[机械工程—光学工程]