基于小波阈值的激光探测声音信号去噪研究

大气与环境光学学报 ›› 2018, Vol. 13 ›› Issue (5): 388-394.

基于小波阈值的激光探测声音信号去噪研究

王行芳，金施群*，侯少阳

(合肥工业大学光电技术研究院，现代显示技术省部共建国家重点实验室，特种显示技术教育部重点实验室，安徽合肥 230009)

出版日期:2018-09-28 发布日期:2018-09-28
作者简介:王行芳(1988-)，女，河南南阳人，研究生，主要从事智能信息处理方面的研究。
基金资助:
Supported by Ministry of Science and Technology of the People’s Republic of China (国家科技部重大科研仪器设备专项,2013YQ220749)

Research on De-noising Method of Laser Detection Sound Signal Based on Wavelet Threshold

WANG Xingfang , JIN Shiqun , HOU Shaoyang

(National Key Laboratory of Advanced Display Technology, Key Laboratory of Special Display Technology of the Ministry of Education，Academy of Photoelectric Technology, Hefei University of Technology, Hefei 230009, China )

Published:2018-09-28 Online:2018-09-28
Supported by:
Supported by Ministry of Science and Technology of the People’s Republic of China (国家科技部重大科研仪器设备专项,2013YQ220749)

摘要/Abstract

摘要：

激光声音探测技术是声音探测领域中重要的研究方向，但该探测技术极易受到背景光、大气湍流等引起的噪声干扰，对探测信号的噪声进行抑制是激光声音探测技术的关键。因此提出一种改进的阈值函数，通过调整参数可以改变小波系数估计值与原小波系数之间的偏差，同时尽量保存信号的特征信息。在实验室环境下通过实验验证了基于所提改进阈值函数的小波阈值去噪法的有效性，探测信号经去噪处理后噪声得到有效去除。

关键词: 激光声音探测技术, 噪声干扰, 阈值函数, 小波阈值去噪

Abstract:

Laser sound detection technology is an important research direction in the field of voice detection, but this detection technology is vulnerable to noise interferences, which are mainly caused by background light and atmospheric turbulence. The study of noise suppression of detection signal is the key of laser sound detection technology. Therefore, an improved threshold function is proposed. By adjusting parameters, the deviation between the wavelet coefficients and the original wavelet coefficients can be changed, and the feature information of the original signals can be preserved as much as possible. In laboratory environment, the effectiveness of wavelet threshold de-noising method based on the improved threshold function is verified by experiments. After de-noising, the noise is effectively removed.

Key words: laser sound detection technology, noise interference, threshold function, wavelet threshold de-noising

中图分类号:

TP391

王行芳金施群侯少阳. 基于小波阈值的激光探测声音信号去噪研究[J]. 大气与环境光学学报, 2018, 13(5): 388-394.

WANG Xing-Fang, JIN Shi-Qun, HOU Shao-Yang. Research on De-noising Method of Laser Detection Sound Signal Based on Wavelet Threshold[J]. Journal of Atmospheric and Environmental Optics, 2018, 13(5): 388-394.

参考文献

[1] Ye Jiaxiong, Xu Qiyang, Fu Xinyao. Detection of laser diffuse reflection echo signal [J]. Chinese Journal of Lasers, 2007, 34(4): 507-510(in Chinese). 叶嘉雄, 徐启阳, 符鑫尧. 探测受声波调制的激光漫反射回波信号[J]. 中国激光, 2007, 34(4):507-510. [2] Kang Honxiang. Study on noise reduction of atmospheric noise and ambient noise in laser acoustic signal [D]. Changsha: Master’s Thesis of University of Defense Science and Technology, 2003(in Chinese). 康宏向. 激光侦听信号中大气噪声与环境噪声的降噪研究 [D]. 长沙: 国防科学技术大学硕士论文, 2003. [3] Han Jiqing, Zhang Lei, Zheng Tieran. Speech Signal Processing [M]. 2nd ed. Beijing: Tsinghua University Press, 2013(in Chinese). 韩纪庆, 张磊, 郑铁然. 语音信号处理. [M]. 第2版. 北京: 清华大学出版社, 2013. [4] Li Congqing, Sun Lixin, Long Dong, et al. Speech denoising method of wavelet transform [J]. Computer Engineering and Applications, 2009, 45(36): 145-147(in Chinese). 李从清, 孙立新, 龙东, 等. 小波变换的语音去噪方法 [J]. 计算机工程与应用, 2009, 45(36): 145-147. [5] Ma Jianfen. Application of wavelet transform in speech denoising [J]. Journal of Taiyuan University of Technology, 2001, 32 (3):238-239(in Chinese). 马建芬. 小波变换在语音去噪中的应用 [J]. 太原理工大学学报, 2001, 32(3): 238-239. [6] Zhang X, Li J, Xing J, et al. A particle swarm optimization technique-based parametric wavelet thresholding function for signal denoising [J]. Circuits Systems & Signal Processing, 2017, 36(1): 247-269. [7] Zhang Defeng. MATLAB Wavelet Analysis [M]. Beijing: Machinery Industry Press, 2009(in Chinese). 张德丰. MATLAB小波分析[M]. 北京: 机械工业出版社, 2009. [8] Donoho D L. Orthonormal ridgelets and linear singularities [J]. Siam Journal on Mathematical Analysis, 1998, 31(5): 1062-1099. [9] Liang Ruiyu, Zhao Li, Wei Xin. The Experimental Course of Speech Signal Processing [M]. Beijing: Machinery Industry Press, 2016. 梁瑞宇, 赵力, 魏昕. 语音信号处理实验教程 [M]. 北京：机械工业出版社, 2016. [10] Donoho D L. De-noising by soft-thresholding [J]. IEEE Transactions on Information Theory, 1995, 41(3): 613-627. [11] Wang Xu, Liu Wensheng, Wang Chang. A study of an improved wavelet threshold de-noising method [J]. Surveying and Mapping Science, 2011, 36(5): 179-180(in Chinese). 王旭, 刘文生, 王昶. 一种改进小波阈值去噪方法的研究 [J]. 测绘科学, 2011, 36(5): 179-180. [12] Qian Y. A Method of Improved Wavelet Threshold for Signal De-Noising [C]// International Conference on Multimedia Technology, IEEE, 2010: 1-3. [13] Wang X. Nonlinear multiwavelet transform based soft thresholding [C]// The 2000 IEEE Asia-Pacific Conference on Circuits and Systems, 2000: 775-778. [14] Deng Yujuan. Research on Speech Threshold Denoising Algorithm Based on Wavelet Transform [D]. Chongqing: Master’s Thesis of Chongqing University, 2009(in Chinese). 邓玉娟. 基于小波变换的语音阈值去噪算法研究 [D]. 重庆: 重庆大学博士论文, 2009.