摘要
针对低信噪比下雷达信号难于识别的问题,提出了基于三维熵特征的雷达信号识别算法。通过提取不同雷达信号的香农熵、指数熵、奇异谱熵特征,利用神经网络分类器,达到对雷达信号进行识别的目的。仿真结果表明,基于三维熵特征的雷达信号识别算法具有较好的抗噪性能,即使在较低的信噪比下,仍具有较好的类内聚集度和类间分离度,可以实现低信噪比对不同的雷达信号进行识别的目的。
It is difficult to identify radar signals under low SNR environment.To deal with this problem,a radar signal recognition algorithm based on three dimensional entropy features is proposed.After extracting characteristics of the Shannon entropy,exponential entropy,and singular spectrum entropy of different radar signals,a neural network classifier is used to achieve classification.Simulation results show that the radar signal recognition algorithm based on three dimensional entropy features has better anti-noise performance.It still has high degree of in-class concentration and separation between different classes even under a low SNR environment.It can achieve the purpose of identifing various radar signals.
出处
《上海电机学院学报》
2015年第3期136-140,共5页
Journal of Shanghai Dianji University
基金
上海电机学院重点学科资助(13XKJ01
A1-1201-14-005)
关键词
雷达信号识别
香农熵
指数熵
奇异谱熵
特征提取
radar signal recognition
Shannon entropy
exponential entropy
singular spectrum entropy
feature extraction
