低信噪比FPPS的弱信号提取与特征识别

Weak signal extraction and feature recognition to polynomial phase signal in low SAR

针对目前电子战中脉压雷达信号淹没在强背景噪声中难以检测提取的现象,在信号相位匹配原理基础上,提出一种改进的弱信号提取模型—单元阵分段信号匹配法来实现对弱信号的提取;在此基础上结合多项式相位信号特点,提出一种改进的特征识别模型——剔除野点的多级中心差分法来实现对脉压雷达信号的特征识别。通过仿真实验表明,该提取识别模型对强白噪声环境下脉压雷达信号的提取与特征识别具有很好的效果。它不需要预先进行训练,并且计算简单易于实现,具有广泛的工程应用前景。

Subsection signals phase matching from single antenna, an improved weak signal extraction mod- el has proposed based on the signal phase matching principle in electronic worfare envhronment in this paper, which aimed at that it＇s extremely difficult to detect and extract the pulse compression radar signal in low SNR at present. Then multilevel central difference scheme eliminating errors, an improved features recognition model has proposed to recognize pulse compression radar signals, combined with the features of polynomial phase sig- nal. The simulation experiment results showed that this extraction and feature recognition model t：an extract and recognize the pulse compression radar signals effectively in low SNR. This new model does not need training simples and is easy to carry out, so it has broad engineering application prospects.