中文摘要：

提出了一种基于改进的希尔伯特-黄变换的电磁信号处理的新方法,该方法适合于在非平稳非线性噪声环境中的电磁辐射的测量。将非平稳信号通过经验模态分解的方法分解为有限个内蕴模式函数,利用自回归模型消除了希尔伯特-黄变换产生的边界效应,进而得到信号的瞬时频率。应用匹配滤波器对背景噪声进行滤除,得到实际电磁辐射信号。由于经验模态分解法的基函数是由信号自适应分解得到的,所以比傅里叶变换以及小波变换得到更好的分解效果。仿真及实验结果表明该方法在非平稳非线性的电磁信号处理中有效地滤除了背景噪声,解决了电磁辐射测量中的环境干扰问题。

英文摘要：

This paper introduces a novel denoising approach used in electromagnetic signal processing based on the improved Hilbert-Huang transform. The method is suitable for electromagnetic radiation measurement in the ambient environment with nonlinear and non-stationary noise. The non-stationary signal is decomposed adaptively into a number of intrinsic mode function （IMF） using empirical mode decomposition （EMD） method. The real electromagnetic radiation signal is obtained through eliminating ambient noise using a matched filter based on EMD. The decomposition is carried out through a sifting process, which produces significantly fewer basis functions than the ones generated by Fourier or wavelet transforms. An autoregressive （AR） model is used to suppress the boundary effect of Hilbert-Huang transform. Simulation and experiment results prove that the proposed approach effectively filters the ambient noise in nonlinear and non-stationary electromagnetic signal processing, and solves the problem of ambient interference in electromagnetic radiation measurement.