摘要
本文提出了一种利用放大器非线性特性来进行特定辐射源识别的多通道相关指纹识别(Multi-Channel Correlation Fingerprinting;MCCF)方法.该方法首先由功率放大器的泰勒级数模型导出窄带输出信号的载频分量和谐波分量表达式,然后利用两分量的关联性,将载频分量作为放大器激励信号的近似,代入谐波分量的表达式中,用最小二乘方法估计出"指纹"特征量.在此基础上本文分析了MCCF的指纹特征的可观测条件和估计的CRLB.该方法定义的指纹特征与放大器的级数模型有关,与激励信号的形式无关,因此是发射机固有的.依据本方法对长沙地区的调频广播的电台进行了"指纹"提取实测实验,在谐波分量功率比载频分量小60到80dB的典型条件下,对四个电台的发射机进行了有效的分类.
A Multi-Channel Correlation Fingerprinting （MCCF） method utilizing the amplifier＇s non-linear property is proposed for specific emitter identification application. From amplifier＇s Taylor series model, we derived the Carrier Component （CC） and Harmonic Component （HC） expressions of the output signal. Then the MCCF method based on the least square algorithm was developed by substituting the CC into the HC as an approximation of the input signal. The observation condition and estimation CRLB of MCCF were provided. The fingerprints of MCCF depend on the Taylor series model, and are independent of the input signals, so they are inherent. The feature extraction experiment of four FM broadcast emitters in Changsha area shows that, the MCCF method works well, even when the HC is 60 to 80dB smaller than the CC.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2008年第5期927-932,共6页
Acta Electronica Sinica
基金
总装预研(No.41101020501)
