摘要
为了提高侦察告警设备中雷达辐射源识别模块的正确识别率,设计了一种基于BP(Back Propagation)网络的雷达辐射源分类器,并就设计关键点——分类器拓扑结构、训练次数的确定以及训练集的设计进行了研究。分类器以BP网络为基础,以载频、脉宽、重频和天线扫描方式为输入特征向量对雷达辐射源进行分类。实验结果证明,该分类器能够对6种不同功能的雷达进行较好的分类,
In order to solve the problem of lower radar emitter recognition rate of radar warning receiver in strong noise background, we design a radar sortation device based on BP (Back Propagation) network, and research on the device structure, training degree and training data design which are the key of radar sortation device. It is based on BP network and uses RF (Radio Freqency), PW (Pulse Width), PRI (Pulse Repetition Interval) and scan mode of antenna as the input eigenvector of BP network to sort radar emitter. Simulation experiment resuits indicate that the recognition rate of radar sortation device can add up to 92. 4% in strong noise background.
出处
《吉林大学学报(信息科学版)》
CAS
2007年第5期525-525,共1页
Journal of Jilin University(Information Science Edition)
基金
空军装备部科研基金资助项目(20060608)
关键词
BP网
雷达辐射源
分类器
back propagation (BP) network
radar sortation devicee
mitter