摘要
在分析雷达测量的空中目标威胁特征指标的基础上,建立了基于概率神经网络的目标类型识别模型。概率神经网络的强大分类能力使得对目标的识别变得迅速、准确。最后,通过算例对文中模型的正确性进行了检验。
On the basis of probabilistic neural network(PNN)and information from surveillance radar,the model for i- dentifying air-targets is established.With the advantage of PNN's strong classification ability,the model can deal with the problem quickly and correctly,and help the commander make decisions effectively.Finally.the correctness of this model is proved by an example.
出处
《弹箭与制导学报》
CSCD
北大核心
2006年第S7期644-646,共3页
Journal of Projectiles,Rockets,Missiles and Guidance
关键词
概率神经网络
分类
目标识别
probabilistic neural network
classification
air-targets identification
