低信噪比下非线性调频信号脉内特征提取新算法

A Novel Method of Extracting the In-pulse Features from NLFM Signal in Low SNR

信号脉内调制信息识别技术对密集和复杂电磁环境中辐射源的分选和识别有着重要意义。通过讨论小波变换法、伪威格纳威尔分布(PWD)法等典型非线性调频信号脉内特征提取方法,提出了将小波变换法和PWD法提取的结果进行截断综合,再提取时频图脊线的新算法。实现了在低信噪比条件下,准确提取非线性调频信号(NLFM)的脉内特征。对不同类型的调制信号仿真结果证实了算法的可行性。

The technique of extracting in-pulse features from compression and complex condition is very important to radiant point selecting and identification. First of all, this paper compares some typical methods of extracting the in-pulse features of NLFM signal, such as wavelet transformation, PWD. Then signal bring it forward a new method based on the colligation of wavelet transformation and PWD, which could extract in-pulse features from NLFM signal in low SNR exactly. The result of the emulation experiments approved the feasibility of this method.