摘要
为了提高脉冲星辐射信号的信噪比,提出了一种基于经验模态分解(EMD)的脉冲星信号去噪算法。利用经验模态分解将信号分解为一组固有模态函数(IMF)。针对EMD阈值消噪算法性能不稳定这一问题,该算法滤除固有模态函数噪声时,利用相邻信号标准差作为噪声水平的判断准则,并采用自适应阈值,对于噪声含量较高的信号采用低通滤波器消噪。实验结果表明,与EMD阈值消噪方法相比,该算法能获得更高的信噪比,并具有较好的稳定性。
In order to improve the signal-to-noise of the pulsar signal,an algorithm of pulsar signal de-noising based on Empirical Mode Decomposition（EMD） is proposed.EMD method decomposes pulsar signal into a group of Intrinsic Mode Functions （IMF）.Aim to the problem that the effect of EMD threshold de-noising is unstable,when IMF is de-noised,variance of near signal is used to obtain the level of noise,and adaptive threshold is used.Signal with noise is de-noised with low pass filter.The simulation results show that compared with EMD threshold de-noising,the proposed algorithm can achieve higher SNR and be stable.
出处
《计算机工程与应用》
CSCD
北大核心
2008年第20期212-214,共3页
Computer Engineering and Applications
基金
中国航天科技集团五院创新基金(No.CAST200629)
863创新基金(No.2006AAJ109)
关键词
脉冲星
EMD
消噪
pulsar
Empirical Mode Decomposition（EMD）
de-noising
