A Complexity-Based Approach for the Detection of Weak Signals in Ocean Ambient Noise
A Complexity-Based Approach for the Detection of Weak Signals in Ocean Ambient Noise
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一种基于复杂性的海洋环境噪声中微弱信号检测方法
DOI：
10.3390/e18030101
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发表时间：
2016-03-01
期刊：
影响因子：
2.7
通讯作者：
Yang, Yixin
中科院分区：
文献类型：
--
作者：
Siddagangaiah, Shashidhar;Li, Yaan;Yang, Yixin
许多研究表明，海洋环境噪声水平在不断增加，对开发检测环境噪声中微弱信号的算法的需求也在不断增长。在这项研究中，我们利用动力学和统计复杂性来检测嵌入在环境噪声中的弱舰船噪声的存在。在南海区中国海面记录了环境噪声和船舶噪声。利用多尺度熵(MSE)方法和复杂性-熵因果平面(C-H平面)分别量化了被测时间序列的动力学复杂性和统计复杂性。我们通过改变舰船信号的放大倍数来产生不同信噪比的信号。仿真结果表明，该算法的复杂度对环境噪声中信息的变化和信噪比的变化很敏感，能够在强背景噪声中检测出微弱的舰船信号。仿真结果还表明，该方法的复杂度优于传统的谱图方法，尤其适用于检测环境噪声中的低信噪比信号。此外，基于复杂性的均方误差和C-H平面方法是简单、稳健的，并且不假定时间序列中的任何潜在动力学。因此，复杂性应该在实际情况中使用。
There are numerous studies showing that there is a constant increase in the ocean ambient noise level and the ever-growing demand for developing algorithms for detecting weak signals in ambient noise. In this study, we utilize dynamical and statistical complexity to detect the presence of weak ship noise embedded in ambient noise. The ambient noise and ship noise were recorded in the South China Sea. The multiscale entropy (MSE) method and the complexity-entropy causality plane (C-H plane) were used to quantify the dynamical and statistical complexity of the measured time series, respectively. We generated signals with varying signal-to-noise ratio (SNR) by varying the amplification of a ship signal. The simulation results indicate that the complexity is sensitive to change in the information in the ambient noise and the change in SNR, a finding that enables the detection of weak ship signals in strong background ambient noise. The simulation results also illustrate that complexity is better than the traditional spectrogram method, particularly effective for detecting low SNR signals in ambient noise. In addition, complexity-based MSE and C-H plane methods are simple, robust and do not assume any underlying dynamics in time series. Hence, complexity should be used in practical situations.