Feature line spectrum extraction of ship radiated noise based on variable mode decomposition optimized by genetic algorithm
Feature line spectrum extraction is an important part of ship target recognition.The traditional detection of envelope modulation on noise(DEMON)spectral analysis method is often used.In the process of processing,the time-domain signal of ship noise is generally not suppressed.In the case of low signal to noise ratio(SNR),the performance of traditional DEMON spectral analysis is poor.In this paper,a genetic algorithm(GA)optimized variational mode decomposition(VMD)method is proposed to decompose the original time-domain signal of ship noise,obtain the reconstructed signal of ship noise after noise suppression,and then effectively extract the amplitude modulation characteristic line spectrum of ship target noise.Firstly,GA is used to optimize the two key inputs of VMD(the number of modes and penalty factor),decompose the VMD to obtain the intrinsic mode function(IMF)of each order,judge,remove the dominant component of noise,and retain the dominant component of signal,so that the reconstructed ship noise signal can significantly suppress the interference noise.Then the target noise modulation characteristic line spectrum is obtained by spectral analysis of the reconstructed signal after noise reduction.The theoretical analysis,simulation and experimental data processing results show that compared with the traditional DEMON spectral analysis method,the GA-VMD based ship noise feature line spectrum extraction method has better noise suppression ability,and the obtained ship noise amplitude modulation feature line spectrum SNR is significantly higher than the traditional DEMON method,which has certain advantages and good prospects.
NETL
NSTL
万方数据
维普
