摘要
针对卫星通信中辐射源信号分类识别问题,开展基于双谱二次特征的卫星通信信号分类识别算法研究。通过辐射源信号的对角切片双谱获取信号特征,利用Chirp-Z变换将双谱对角切片特征从频域扩展至复平面,并提出扩展的基于巴氏(Bhattacharyya)距离的分离度准则作为信号双谱二次特征提取依据,提取出具有最强可分离度特征作为特征参数,并通过支持向量机进行分类识别仿真实验。实验表明,该识别算法适用于不同类型的卫星通信信号,且对噪声变化不敏感,可实现较高的正确识别率。
To deal with the problem of signal identification in satellite communication, this paper developed a new identification algorithm based on bispeetrum cascade feature. It could obtain signal feature by analyzing the diagonal slice of the spectrum. By using Chirp-Z transform, the algorithm enlarged the diagonal slice of the spectrum from the frequency domain to the Z-plane. It extracted bispectrum cascade feature according to the extended Bhattacharyya distance measurement and obtained the most powerful detachable features as the feature parameters. By support vector machine （SVM）, this paper simulated the processing of signal identification. The results show that the method is suitable for different types of communication signals. The algorithm is not sensitive to noise and can achieve high identification accuracy.
出处
《计算机应用研究》
CSCD
北大核心
2017年第6期1835-1837,1841,共4页
Application Research of Computers
基金
国家自然科学基金资助项目(61271353)
安徽省自然科学基金资助项目(1408085MF120)
关键词
卫星通信
特征提取
分类识别
复双谱对角切片
巴氏距离
satellite communication
feature extraction
classification and identification
diagonal slice of complex bispectrum
Bhattacharyya distance measurement
