基于免疫RBF网络阵列的雷达信号分类识别方法  

A Novel Recognition Method of Radar Signals Based on immune RBF Network Array

作　　者：臧小刚[1] 宫新保[1] 凌小峰[1] 常成[1] 

机构地区：[1]上海交通大学电子工程系,上海200240

出　　处：《信号处理》2009年第7期1146-1149,共4页Journal of Signal Processing

基　　金：上海-NRC-IRAP合作计划(No.06SN07112)

摘　　要：本文提出了基于免疫算法设计的径向基函数(RBF)网络阵列实现对雷达信号体制和用途的分类识别。同单个神经网络相比,这种方法克服了识别类型较多时存在的扩充、修改、维护等难点。在RBF子网络的训练中,采用结合记忆机制的递阶免疫算法确定RBF网络的隐层参数,有效折衷了系统性能和运算量之间的矛盾。实验结果表明,采用这种方法设计的雷达信号识别系统达到了很高的性能。In this paper,radial basis function （RBF） network array designed by immune algorithm is proposed to the recognition of type and application of intercepted radar signals. Compared to single neural network, the method overcomes the difficulties of expansion, modification and maintenance when there are a large number of radar styles. In the training of RBF sub-network, hierarchical immune algorithm combined with memory mechanism is used to determine RBF hidden layer parameters ,which effectively compromise between performance and computation load. Experimental results demonstrate that the recognition system designed by the proposed method has reached very high performance.

关 键 词：雷达信号识别 径向基函数网络 神经网络阵列 递阶免疫算法 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TN95[自动化与计算机技术—控制科学与工程]