文章摘要
赵杰,杨英,惠力,王志,初士博,刘茂科.小波包节点分段阈值降噪在水声监听中的应用*[J].,2019,38(6):1015-1024
小波包节点分段阈值降噪在水声监听中的应用*
Wavelet packet node segmental threshold denoising for underwater acoustic monitoring
投稿时间:2019-01-16  修订日期:2019-10-29
中文摘要:
      水声信号在发送、传播、接收及处理过程中,很容易受到环境噪声、电子电路系统自噪声等方面的影响,会使实际数据含有大量噪声信号。为保证获得水声信号的准确性及后续反演工作的可靠性,在已有的小波分析的基础上,提出小波包节点相对能量判断最优分解层,最优分解层节点系数处理重构的方法应用于水声信号去噪中。该方法打破小波阈值去噪高频处理方面的局限性,提高水声信号的识别精度,有效改善全局单一阈值规则去噪存在的短板,实验结果表明,该方法获得的最优分解层是可靠的,在最优分解层进行节点分段阈值处理可以将噪声频段信号与目标信号频段有效分离,与其他小波方法对比分析,对监听获得的100-50000hz范围内水声信号处理上,具有较好的分离与降噪能力。
英文摘要:
      Underwater acoustic signal is easily affected by environmental noise and self-noise of electronic circuit system and so on, which will make the actual data contain a large number of noise signals in the process of transmitting,receiving and processing.In order to ensure the accuracy of underwater acoustic signal and the reliability of subsequent inversion work, the wavelet packet node relative energy for judging optimal decomposition layer and node coefficient multi-segment threshold processing reconstruction method is proposed for underwater acoustic signal denoising,which is based on the existing wavelet analysis.This method,which can increase the recognition accuracy ,breaks the imitation of wavelet threshold denoising processing in the high frequency, meanwhile improves the short-board of global single threshold denoising.The experimental results show that the optimal decomposition layer obtained by this method is reliable. Node segmentation threshold processing in the optimal decomposition layer can effectively separate the noise band signal from the target signal band.Compared with other wavelet methods, it has better separation and de-noising ability in underwater acoustic signal processing in the range of 100-50000 Hz.
DOI:10.11684/j.issn.1000-310X.2019.06.015
中文关键词: 小波包分析  最优分解层  水声监听信号  分段阈值去噪
英文关键词: Wavelet packet analysis  Optimal decomposition layer  Underwater acoustic monitoring signal  multi-segment threshold
基金项目:
作者单位E-mail
赵杰 齐鲁工业大学山东省科学院 zhaojie83@126.com 
杨英 齐鲁工业大学山东省科学院 31453552@qq.com 
惠力 齐鲁工业大学山东省科学院 11932807@qq.com 
王志 齐鲁工业大学山东省科学院 704522113@qq.com 
初士博 齐鲁工业大学山东省科学院 48742109@qq.com 
刘茂科 齐鲁工业大学山东省科学院 xiaoyaolong333@163.com 
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