Target Detection Method of Underwater Acoustic Signals Based on Energy Entropy of Empirical Mode Decomposition
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摘要: 为了解决复杂环境中水声目标难以有效检测的问题，提出了一种新的基于经验模式分解(EMD)能量熵的水声目标检测方法。该方法通过对水声信号进行经验模式分解，提取信号的本征模式分量并转化为能量特征向量，从而观测子频带能量特征的变化；然后由能量特征向量计算出经验模式能量熵，实现了对水声目标的检测。将该方法应用在仿真和实测的水声目标辐射噪声数据的目标检测中，测试结果表明，与小波变换方法相比，该方法不仅能有效地得到水声信号子频带的能量特征，而且还极大地优化了水声目标检测的区间。
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关键词:
- 经验模式分解（EMD) /
- 能量熵 /
- 水声信号 /
- 目标检测
Abstract: In order to correctly detect the acoustic signals of underwater target in complicated environment, a novel target detection method of underwater acoustic signals based on energy entropy of empirical mode decomposition (EMD) is proposed, where these intrinsic mode components are decomposed via empirical mode decomposition from original signals and converted into energy feature vectors, and thus the energy features of sub-band frequency can be inspected. The energy entropy of EMD is obtained from these normalized energy feature vectors to detect the target of underwater acoustic signals. The proposed method is applied to the target detection of simulation signal and radiated noise data of underwater target. The experimental results show that this method can effectively obtain the energy feature of sub-band frequency, and greatly optimize the target detection threshold of underwater acoustic signals compared with the wavelet transform method. -
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