摘要
目前常用的雷达辐射源识别方法是数据库比较查询法,该方法实现简单,易于工程实践,但其识别效率取决于数据库的容量和质量,即对先验知识的依赖性强,缺少推理,灵活性差,特别是对于许多新体制雷达信号无法很好地识别。将利用模糊匹配和RBF神经网络两种算法,设计一种识别系统,该识别系统能够较好地识别复杂体制雷达信号,能应对目前雷达辐射源数据库不完善的实际情况。实验仿真表明,该识别系统具有较高的识别率,是一种可行的雷达辐射源识别方法。
The database comparision query method is a common method to recognize the radar emitter presently. This method can be simply realized and performed in engineering, but its recognition efficiency lies on the capability and quality of the database, which means that it depends on the known information much and lacks of reasoning ＆ agility, specially it can not recognize a lot of new system radar signal well. This paper designs a kind of recognition system by using two algorithms： fuzzy matching and radial basis function（RBF） neural network. This recognition system can recognize the radar signal of complicated system well and cope with the present practical states of incomplete radar emitter database. The experiment simulation shows that the recognition system has the superior recognition rate,and is a feasible recognition method to the radar emitter.
出处
《舰船电子对抗》
2009年第4期57-62,共6页
Shipboard Electronic Countermeasure
关键词
雷达辐射源识别
模糊匹配
径向基函数神经网络
radar emitter recognition
fuzzy matching
radial basis function neural network
