摘要
提出一种基于小波与神经网络联合分析的雷达辐射源信号分选新方法.该方法首先对接收到的雷达信号进行小波去噪,达到提高信噪比的目的,然后利用小波脊线法准确提取其脉内特征参数,最后基于神经网络实现信号的分选.计算机仿真结果表明,较现有方法,该方法在较低的信噪比情况下,可以更准确地实现雷达辐射源信号的分选.
A new method for sorting radar emitter signals is proposed in this paper. In order to improve Signal noise ratio （SNR）, Wavelet Denoising is used, and the radar in-pulse characteristics is extracted by Wavelet-ridge, radar emitter signal sorting is realized by neural networks. By simulation, it shows that this method can realize precise sorting under low SNR, and it is better than other methods.
出处
《武汉理工大学学报（交通科学与工程版）》
2007年第3期430-433,共4页
Journal of Wuhan University of Technology（Transportation Science & Engineering）
基金
国防预研基金项目资助(批准号:51437030105HK101)
关键词
小波去噪
脉内特征
神经网络
信号分选
wavelet denoising
in pulse characteristics
neural networks
signal sorting
