基于改进 EMD 方法与 1 1/2 谱的 DEMON 谱提取方法

Detection of envelope modulation on noise (DEMON) spectrum analysis method has been widely used in the field of feature extraction, but how to select the frequency band of high frequency signals in classical DEMON spectrum extraction is a problem that affects the extraction effect of DEMON spectrum. In order to solve this problem, the empirical mode decomposition (EMD) method is used to obtain a series of intrinsic mode functions, and then more representative intrinsic mode functions are selected for demodulation according to the degree of correlation between each mode function and the original signal. The demodulated result is then analyzed by 1 1/2 spectrum analysis method to suppress Gaussian noise. The obtained DEMON spectrum result has a better signal to noise ratio than the traditional method. The analysis results of the measured lake test data show that the improved method can effectively extract features, and the results are better than that of the classical DEMON spectral analysis method. The improved method has certain practicality and is more conductive to the subsequent target classification and recognition.