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%。
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 fil- tered 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 likeli- hood function. Computer simulation results show that the method is able to classify the two same model radar e- mitters by single pulse information with an accuracy rate of 94% when SNR is 0 dB and the correlation coeffi- cient is 0. 993 2.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2009年第2期270-273,共4页
Systems Engineering and Electronics
关键词
特定辐射源识别
卡亨南一洛维展开
长球面函数
最大似然准则
specific emitter recognition
Karhunen-Loeve transformation
speroidal wave functions
maxi- mum- likelihood criterion
