基于最大似然准则的特定辐射源识别

Journal of Systems Engineering and Electronics ›› 2009, Vol. 31 ›› Issue (2): 270-273.

基于最大似然准则的特定辐射源识别

胡国兵^1,2, 刘渝¹

1. 南京航空航天大学信息科学与技术学院, 江苏, 南京, 210016;
2. 南京信息职业技术学院电子信息工程系, 江苏, 南京, 210046

收稿日期:2007-10-07 修回日期:2008-02-14 出版日期:2009-02-20 发布日期:2010-01-03
作者简介:胡国兵(1978- ),男,讲师,博士研究生,主要研究方向为信号与信息处理.E-mail:guobinghu@163.com

Specific radar emitter recognition based on maximum-likelihood criterion

HU Guo-bing^1,2, LIU Yu¹

1. Coll. of Information Science and Technology, Nanjing Univ. of Aeronautics & Astronautics, Nanjing 210016, China;
2. Dept. of Electronic Information Engineering, Nanjing Coll. of Information Technology, Nanjing 210046, China

Received:2007-10-07 Revised:2008-02-14 Online:2009-02-20 Published:2010-01-03

摘要/Abstract

摘要： 在信号包络存在细微差异前提下,研究了基于最大似然准则的特定辐射源识别算法.先将接收信号进行滤波,滤除带外噪声,以提高信噪比,接着将处理后的具有带限白噪声背景的信号变换到基带并进行卡亨南-洛维展开,在此基础上对信号的似然函数进行处理,得到等效的检验统计量及判决门限,完成特定辐射源的分类识别.计算机仿真表明,被识别信号的互相关系数为0.9932时,在0 dB信噪比条件下,利用单个脉冲信息,平均识别正确率达94%.

Abstract: Based on the small differences between envelopes of the two specific signals,a new radar emitter recognition method is presented according to the maximum-likelihood criterion.Firstly,the received signal is filtered to reduce the noise out of the bandwidth and to enhance the signal-to-noise ratio.Consequently,the signal with additive band-limited white noise is transformed to baseband and is expanded in K-L(Karhunen-Loeve) series.Specific radar emitter recognition is performed by the equivalent decision variable inferred from the likelihood function.Computer simulation results show that the method is able to classify the two same model radar emitters by single pulse information with an accuracy rate of 94% when SNR is 0 dB and the correlation coefficient is 0.9932.

中图分类号:

TN957

胡国兵, 刘渝. 基于最大似然准则的特定辐射源识别[J]. Journal of Systems Engineering and Electronics, 2009, 31(2): 270-273.

HU Guo-bing, LIU Yu. Specific radar emitter recognition based on maximum-likelihood criterion[J]. Journal of Systems Engineering and Electronics, 2009, 31(2): 270-273.

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