噪声的包络调制检测(Detection of Envelope Modulation on Noise,DEMON)谱分析技术已被广泛应用于特征提取领域,但经典DEMON谱提取中高频信号频段的选取会影响DEMON谱的提取效果.针对这一问题,文中首先运用经验模态分解(Empirical Mode Decomposition,EMD)方法获得一系列固有模态函数(Intrinsic Mode Function,IMF),依据各阶模态函数与原信号的相关程度,筛选出更具代表性的几阶固有模态函数进行解调,再对解调的结果运用11/2维谱分析方法进行谱分析以抑制高斯噪声,通过这种方法获得的DEMON谱信噪比优于传统方法.实测湖试数据分析结果表明,该改进方法可以有效地进行特征提取,结果优于经典DEMON谱分析方法;该改进方法具有一定的实用性,有利于进行后续目标分类识别.
DEMON spectrum extraction method based on improved EMD method and 11/2 spectrum analysis
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 11/2 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.
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