基于Earley剖析的多功能雷达文法参数估计算法  

Grammar parameter estimation algorithm of multi-function radars based on Earley parsing

作　　者：曹帅[1] 王布宏[1] 李龙军[1] 李夏[1] Cao Shuai Wang Buhong Li Longjun Li Xia(College of Information ＆ Navigation, Air Force Engineering University, Xi＇ an 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：《计算机应用研究》2017年第9期2758-2762,共5页Application Research of Computers

基　　金：国家自然科学基金资助项目(61172148);航空基金资助项目(20112090616)

摘　　要：针对基于随机上下文无关文法(stochastic context-free grammar,SCFG)建模的多功能雷达(multi-function radars,MFR)参数估计问题的研究,在原有inside-outside(IO)算法和viterbi-score(VS)算法的基础上,提出一种基于Earley剖析的多功能雷达文法参数估计算法——EIO算法。该算法将IO算法与Earley剖析相结合,通过对截获的雷达数据进行预处理,可以处理任意形式的文法产生式,对文法产生式概率进行学习,从而实现MFR文法参数估计。通过理论分析和实验仿真,EIO算法可以在减少计算复杂度、记忆复杂度和运行时间的同时,有效保持文法参数估计精度,论证了该方法的正确性和有效性。To deal with the parameter estimation problem in multi-function radars （MFR） based on stochastic context-free grammar（SCFG） model, this paper developed a new method of MFR parameter estimation problem based on Earlcy parsing called EIO algorithm on the basis of traditional inside-outside （IO） algorithm and viterbi-score （VS） algorithm. This method pre-processed the intercepted radar data by combining I0 algorithm with Earley parsing to handle arbitrary grammar production rules. It utilized the EIO algorithm to realize the learning of grammatical production rules probabilities and MFR parameter estimation. Theoretical analysis and simulation results show that the modified algorithm can reduce the computation complexity, memory complexity and running time while keeping the same level of estimation accuracy, validates the correctness and et＇fee- tiveness of this method.

关 键 词：随机上下文无关文法 多功能雷达 参数估计 Earley剖析 文法产生式 

分 类 号：TN958.91[电子电信—信号与信息处理]