摘要
针对传统的通信对抗干扰效果评估方法无法在战时进行实时评估的问题,提出一种基于GA-ELM的在线评估方法。以Link-16为干扰研究对象,首先分析选取其抗干扰行为参数,建立样本库,之后利用极限学习机(ELM)对样本参数进行分类学习,同时使用改进的遗传算法(GA)优化ELM,得到GA-ELM模型。实验结果表示,使用GA-ELM在线评估方法,以抗干扰行为参数为依据,能够得出干扰效果在线评估结果。新方法克服了传统方法无法应用于战时的缺点,更加贴近实战。
Traditional methods for jamming effect evaluation in communication countermeasure cannot be applied to real-time evaluation in wartime.To solve the probleman online evaluation method based on GA-ELM is proposed.Link-16 is taken as the research object.Firstlythe parameters of its anti-jamming behavior are analyzed and selected to build a sample library.ThenELM is used to learn the sample parameters after classificationand the improved GA is used to optimize ELMso that the GA-ELM model is obtained.Experimental results show that GA-ELM can obtain online evaluation results of jamming effect based on the parameters of anti-jamming behavior.The new method overcomes the shortcoming of the traditional methodsand is more close to actual combat.
作者
汪慧阳
刘松涛
赵帅
WANG Huiyang;LIU Songtao;ZHAO Shuai(Department of Information System,Dalian Naval Academy,Dalian 116000,China)
出处
《电光与控制》
CSCD
北大核心
2021年第12期71-75,80,共6页
Electronics Optics & Control
基金
博士后基金(2015M572694,2016T90979)。
关键词
通信对抗
干扰效果
在线评估
极限学习机
遗传算法
communication countermeasure
jamming effect
online evaluation
Extreme Learning Machine(ELM)
Genetic Algorithm(GA)