基于随机无穷自动机的多功能雷达辐射源识别方法  

Multi-function radar emitter identification based on stochastic infinite automaton

作　　者：曹帅[1] 王布宏[1] 李龙军[1] 刘帅琦 CAO Shuai WANG Buhong LI Longjun LIU Shuaiqi(Information and Navigation College, Air Force Engineering University, Xi＇an Shaanxi 710077, China)

机构地区：[1]空军工程大学信息与导航学院,西安710077

出　　处：《计算机应用》2017年第2期608-612,共5页journal of Computer Applications

基　　金：国家自然科学基金资助项目(61172148)~~

摘　　要：针对基于随机上下文无关文法(SCFG)建模的多功能雷达(MFR)辐射源识别问题,提出了一种基于随机无穷自动机(SISA)的MFR辐射源识别方法。在文法建模的基础上,对"水星"MFR控制模块文法产生式和系统特征文法产生式进行重新构造生成SCFG,利用SCFG构造随机无穷自动机作为识别器,从而实现对测量辐射源的识别。通过理论分析和实验仿真得出:该方法能实现对MFR辐射源的识别;在一定范围内,通过增加文法产生式个数,可以提高平均识别率,且识别性能优于通过SCFG构造的随机下推自动机(SPDA)。实验结果表明了该方法的正确性和有效性。To deal with the emitter identification problem in Multi-Function Radar （MFR） based on Stochastic Context- Free Grammar （SCFG） model, a MFR emitter identification method based on Stochastic Infinite State Automata （SISA） was proposed on the basis of syntactic modeling. The grammar production rules in ＂Mercury＂ MFR control module and the characteristic production rules in ＂Mercury＂ MFR system were used in this method to reconstruct an SCFG, which was further used to construct an SISA for identification subsequently. Theoretical analysis and simulation results show that the proposed method can realize MFR emitter identification. Within a certain range, the average recognition rate can be improved by adding the amount of grammar production rules, and the identification performance is superior to Stochastic Push-Down Automata （SPDA） constructed by SCFG. The experimental resuhs validate the reliability and effectiveness of the proposed method.

关 键 词：随机上下文无关文法 多功能雷达 辐射源识别 随机无穷自动机 文法产生式 

分 类 号：TN958.92[电子电信—信号与信息处理]