一种新的ESM数据分选算法  

A New ESM Data Sorting Algorithm

作　　者：戴天[1] 郭贵虎[1] 杨庆[1] 

机构地区：[1]91635部队

出　　处：《计算机仿真》2010年第12期5-7,39,共4页Computer Simulation

摘　　要：研究获取敌方雷达辐射源数据,在识别准确性问题上,ESM数据分选在电子侦察领域有重要的作用。针对辐射源识别的正确性,采用聚类和到达角外推相结合方法实现ESM数据分选,提出一种基于支持向量机和到达角外推的ESM数据分选算法。算法根据ESM数据辐射源参数信息,用支持向量机实现ESM数据聚类,根据其参数实现分类,再将信号到达角外推,预测信号下一时刻到达角,并以最近邻域关联准则将信号方位角关联,从而实现ESM数据分选。算法有效结合了辐射源参数特征和到达角变化趋势,可在辐射源较密集的环境下实现分选。仿真结果和实际数据测试表明了算法的有效性。ESM data sorting is widely applied in electronic reconnaissance,which is the base of radar emitter recognition and data fusion.To improve the correctness of the recognition,with a method synthesized clustering and AOA tracking,an algorithm based on Support Vector Machine and AOA extrapolation is proposed.This algorithm takes advantage of radar emitter parameters,clusters with SVM,and classifies the ESM data.Then,by extrapolating AOA,predicting future AOA and associating data with NNDA rule,ESM data are sorted.This algorithm utilizes radar emitter parameters and trend of emitter AOA,so it works in dense radar emitter environment.Simulation and experiments have proved the validity of this algorithm.

关 键 词：电子支援 分选 支持向量机 到达角外推 

分 类 号：TN791[电子电信—电路与系统]