邸忆,顾晓辉,车龙,刘亚雷.基于改进EEMD及能量特征的战场目标识别方法[J].电子测量与仪器学报,2017,31(6):914-921
基于改进EEMD及能量特征的战场目标识别方法
Battlefield target recognition method based on improved EEMD and energy feature
  
DOI:10.13382/j.jemi.2017.06.014
中文关键词:  目标识别分类  总体经验模态分解  高低频能量差  能量向量  能量特征分析
英文关键词:target recognition and classification  ensemble empirical mode decomposition  energy difference between the high and low frequency  energy vector  energy feature analysis
基金项目:国家自然科学青年基金(61401105)、浙江省教育厅项目(Y201533894)资助
作者单位
邸忆 南京理工大学机械工程学院南京210094 
顾晓辉 南京理工大学机械工程学院南京210094 
车龙 南京理工大学机械工程学院南京210094 
刘亚雷 公安海警学院宁波315801 
AuthorInstitution
Di Yi School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China 
Gu Xiaohui School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China 
Che Long School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China 
Liu Yalei China Maritime Police Academy, Ningbo 315801, China 
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中文摘要:
      针对战场声目标探测系统对目标识别及分类问题,提出了一种基于频率截止EEMD(cut off frequency EEMD,CF EEMD)的能量特征分析(energy feature analysis,EFA)方法。选取信号自身的最小有效频率作为EEMD筛分的终止条件,对EEMD方法进行改进,实现目标声信号的快速分解,获得准确的IMF分量;通过计算各阶IMF能量,得到目标信号的总体能量向量,进而分析典型目标声信号各阶IMF分量的能量分布情况;定义目标声信号高低频段能量差特征参数,用于战场声目标的特征识别与分类。半实物仿真试验结果证明了CF EEMD与EFA相结合的目标声信号识别方法的可行性和实用性,适用于战场声目标识别及分类。
英文摘要:
      In order to solve the target recognition and classification problem of battlefield acoustic target detection system, an energy feature analysis (EFA) method based on cut off frequency EEMD (CF EEMD) is proposed. Selecting the minimum effective frequency of the signal itself as screening termination condition of EEMD, the EEMD method is improved to achieve rapid decomposition of acoustic target and get accurate IMF components. The total energy vector of the target signal is obtained by calculating the energy of each IMF, and then the energy distribution of each IMF component of the typical target acoustic signal is analyzed. The energy difference between the high and low frequency of the target acoustic signal is defined, which is used as feature parameter to identify and classify the battlefield acoustic target. Through the semi physical simulation experiment the feasibility and the practicality of the EFA based target recognition method with improved EEMD is verified, which is suitable for identification and classification of battlefield acoustic target.
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