Pulse Repetition Interval Modulation Recognition Based on Frequencies and Patterns
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摘要: 根据雷达信号脉冲序列的特点,从雷达脉冲信号中提取频率特征和形状特征,构成二维特征向量,并用支持向量机设计多类别分类器,实现雷达信号PRI调制信号的自动识别,实验结果表明,对特征向量进行大幅度降维(从64维降到2维)后,既简化了分类器,又保持或提高了识别率和抗噪声性能.与原特征向量相比,对无噪样本的误识率从0.15%-0.25%降低到0.00%,对有噪样本的误识率从0.40%-1.30%降低到0.15%-0.93%.Abstract: According to the characteristics of pulse trains of radar signals, frequency and pattern are extracted from radar emitter signals.The two features constitute two-dimensional vectors, which are taken as inputs of a classifier designed by a support vector machine to identify the pulse repetition interval modulation of radar emitter signals automatically.Experimental results show that when the dimensions are lowered from 64 to 2, the extracted feature vector decreases the complexity of the classifier while maintaining or even enhancing the performances in recognition rate and noise suppression.Comparing to the original feature vector, the error rate of recognition of the extracted feature vector decreases from 0.15%-0.25% to 0.00% for the samples without noises, and from 0.40%-1.30% to 0.15%-0.93% for noised ones.
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Key words:
- recognition /
- radar signal /
- pulse repetition interval /
- support vector machine /
- frequency /
- pattern
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NOONE G P.A neural approach to automatic pulse repetition interval modulation recognition[C]// Proceedings of International Conference on Information,Decision and Control,1999,213-218.[2] 张葛祥,荣海娜,金炜东.支持向量机在雷达辐射源信号识别中的应用[J].西南交通大学学报,2006,41(1):25-30.ZHANG Gexiang,RONG Haina,JIN Weidong.Application of support vector machine to radar emitter signal recognition[J].Journal of Southwest Jiaotong University,2006,41 (1):25-30.[3] ZHANG Gexiang,RONG Haina,JIN Weidong,et al.Radar emitter signal recognition based on resemblance coefficient features[C]// Lecture Notes in Artificial Intelligence.Berlin:Springer Verlag,2004,3066:665-670.[4] 王伟,杨晓玲.一种基于TOA差值矩阵的辐射源识别方法[J].航天电子对抗,2004,(1):48-51.WANG Wei,YANG Xiaoling.An emitter recognition inethod based on TOA difference matrix[J].Aerospace Electronic Warfare,2004,(1):48-51.[5] NOONE G P.A neural approach to tracking radar pulse repetition interval modulation[C]//Proceedings of 6th International Conference on Neural Information Processing,1999,3:1 075-1 080.[6] MARDIA H K.New technique for the deinterleaving of repetitive sequences[J].IEE Proceedings,Part F:Communications,Radar and Signal Processing,1989,136(4):149-154.[7] MILOJEVIC D J,POPOVIC B M.Improved algorithm for the deinterleaving of radar pulses[J].IEE proceedings,Part F:Radar and Signal Processing,1992,139(1):98-104.[8] VAPNIK V.Statistical learning theory[M].许建华,张学工,译.北京:电子工业出版社,2004.[9] HSU C W,LIN C J.A comparison of methods for multiclass support vector machines[J].IEEE Transactions on Neural Networks,2002,13(2):415-425.[10] FURNKRANZ J.Round robin classification[J].Journal of Machine Learning Research,2002,2(4):721-747.[11] ZADROZNY B.Reducing multiclass to binary:a unifying approach for margin classifiers[J].Journal of Machine Learning Research,2001,1(2):113-141.[12] PLATT J C,CRISTIANINI N,SHAWE T J.Large margin DAGs for multiclass classification[C]// Advances in Neural Information Processing System.MIT Press,2000,547-553.
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