华中科技大学学报（自然科学版）2024，Vol.52Issue(4)：88-93,6.DOI:10.13245/j.hust.240708
基于MEFD-小波阈值降噪的舰船电场特征提取
Feature extraction of ship shaft electric field based on MEFD-wavelet threshold denoising
摘要
Abstract
To realize feature extraction of ship shaft-rate electric field at low signal-noise ratio(SNR),a feature extraction method based on modified empirical Fourier decomposition(MEFD)-wavelet threshold was proposed.First,the MEFD which introduced the auto regressive and moving average model(ARMA)was adopted to separate signal from noise.Then,the L2-norm was calculated to screen out the efficient information components.Finally,the following components were processed by wavelet threshold denoising.To verify the feasibility of the proposed method,the simulation signatures and ship model measured signatures were conducted.Experimental results show that the proposed method is robust to the environmental noise.The index of orthogonality is 0.001 5,and similarity index is 0.450 3 in the extracting result of 2B distance in ship model experiment,which has better performance of feature extraction than other methods.The proposed method can detect the electric field signatures in a longer distance and lay a good foundation for the subsequent analysis and application of electric field characteristics.关键词
轴频电场/改进经验傅里叶分解/小波阈值去噪/L2范数/特征提取Key words
shaft-rate electric field/modified empirical Fourier decomposition/wavelet threshold denoising/L2 norm/feature extraction分类
信息技术与安全科学引用本文复制引用
胡育诚,王向军,汪石川..基于MEFD-小波阈值降噪的舰船电场特征提取[J].华中科技大学学报（自然科学版）,2024,52(4):88-93,6.基金项目
国家自然科学基金资助项目(41476153). （41476153）
