水下目标声散射信号的时频域盲抽取

杨阳; 李秀坤

doi:10.7498/aps.65.164301

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名

邮箱

手机号码

标题

留言内容

验证码

摘要

目标声散射机理及其散射特性为识别目标的物理依据. 针对水下目标声散射成分在时-频域存在相互混叠干扰，造成目标弹性声散射特征不稳定的问题，提出一种适合在欠定问题下分离目标声散射成分的时频域盲抽取方法. 研究声散射成分的时频特征差异，构造目标回波单源自项的空间时频分布矩阵，通过对其进行特征值分解抽取相应的声散射成分，建立描述目标声散射物理特性的信号模型. 抽取出的目标各弹性波分量与以表面环绕波产生理论计算结果相符. 仿真与消声水池实验数据处理结果表明，该算法可以分离出目标回波的各个声散射成分，提高了分离信号的输出信噪比，为水下目标识别提供稳定和可靠的特征.

关键词:

作者及机构信息

杨阳^{1 2},
李秀坤^{1 2}

1.
哈尔滨工程大学, 水声技术重点实验室, 哈尔滨 150001;

2.
哈尔滨工程大学水声工程学院, 哈尔滨 150001

通信作者: 李秀坤, lixiukun@hrbeu.edu.cn

基金项目: 国家自然科学基金（批准号：51279033）和黑龙江省自然科学基金（批准号：F201346）资助的课题.

参考文献

[1]	La Follett J R, Williams K L, Marston P L 2011 J. Acoust. Soc. Am. 43 669
[2]	Williams KL, Kargl SG, Thorsos 2010 J. Acoust. Soc. Am. 127 6
[3]	Espana A, Williams K L, Plotnick D S 2013 J. Acoust. Soc. Am. 9 1
[4]	Bucaro J, Houston B, Saniga M, Dragonette L, Yoder T, Dey S, Kraus L, Carin L 2008 J. Acoust. Soc. Am. 123 738
[5]	Fan J 2001 Ph. D. Dissertation (Shanghai: Shanghai Jiaotong University) (in Chinese) [范军 2001 博士学位论文(上海: 上海交通大学)]
[6]	Pan A, Fan J, Wang B 2013 J. Acoust. Soc. Am. 134 3452
[7]	Pan A, Fan J, Wang B, Chen Z G, Zheng G Y 2014 Acta Phys. Sin. 63 214301 (in Chinese) [潘安, 范军, 王斌, 陈志刚, 郑国垠 2014 物理学报 63 214301]
[8]	Zheng G Y, Fan J, Tang W L 2010 Acta Acustica 35 31 (in Chinese) [郑国垠, 范军, 汤渭霖 2010 声学学报 35 31]
[9]	Anderson S D 2012 Ph. D. Dissertation (Georgia Institute of Technology)
[10]	Anderson S D, Sabra K G, Zakharia M E, Sessarego J P 2012 J. Acoust. Soc. Am. 131 164
[11]	Li X K, Meng X X, Xia Z 2015 Acta Phys. Sin. 64 064302 (in Chinese) [李秀坤, 孟祥夏, 夏峙 2015 物理学报 64 064302]
[12]	Xia Z, Li X K 2015 Acta Phys. Sin. 64 094302 (in Chinese) [夏峙, 李秀坤 2015 物理学报 64 094302]
[13]	Li F H, Zhang Y J, Zhang R H, Liu J J 2010 Phys. Sci. China 53 1408
[14]	Zhu N, Wu S 2009 J. Acoust. Soc. Am. 126 2254
[15]	Bouaynaya N, Charif-Chefchaouni M, Schonfeld D 2008 IEEE Trans. Pattern Anal. Mach, Intell. 30 5
[16]	Tang W L, Fan J 2004 Acta Acustica 29 5 (in Chinese) [汤渭霖, 范军 2004 声学学报 29 5]
[17]	Tesei A, Fawcett J A, Lim R 2008 Appl. Acoust. 69 422
[18]	Touraine N, Haumesser L, De’cultot D, Maze G 2000 J. Acoustic Soc. Am. 108 5
[19]	Tang W L 1994 Acta Acustica 19 92 (in Chinese) [汤渭霖 1994 声学学报 19 92]
[20]	Thomas M, Lethakumary B, Jacob R 2012 ICCEET p717

施引文献

[1]	La Follett J R, Williams K L, Marston P L 2011 J. Acoust. Soc. Am. 43 669
[2]	Williams KL, Kargl SG, Thorsos 2010 J. Acoust. Soc. Am. 127 6
[3]	Espana A, Williams K L, Plotnick D S 2013 J. Acoust. Soc. Am. 9 1
[4]	Bucaro J, Houston B, Saniga M, Dragonette L, Yoder T, Dey S, Kraus L, Carin L 2008 J. Acoust. Soc. Am. 123 738
[5]	Fan J 2001 Ph. D. Dissertation (Shanghai: Shanghai Jiaotong University) (in Chinese) [范军 2001 博士学位论文(上海: 上海交通大学)]
[6]	Pan A, Fan J, Wang B 2013 J. Acoust. Soc. Am. 134 3452
[7]	Pan A, Fan J, Wang B, Chen Z G, Zheng G Y 2014 Acta Phys. Sin. 63 214301 (in Chinese) [潘安, 范军, 王斌, 陈志刚, 郑国垠 2014 物理学报 63 214301]
[8]	Zheng G Y, Fan J, Tang W L 2010 Acta Acustica 35 31 (in Chinese) [郑国垠, 范军, 汤渭霖 2010 声学学报 35 31]
[9]	Anderson S D 2012 Ph. D. Dissertation (Georgia Institute of Technology)
[10]	Anderson S D, Sabra K G, Zakharia M E, Sessarego J P 2012 J. Acoust. Soc. Am. 131 164
[11]	Li X K, Meng X X, Xia Z 2015 Acta Phys. Sin. 64 064302 (in Chinese) [李秀坤, 孟祥夏, 夏峙 2015 物理学报 64 064302]
[12]	Xia Z, Li X K 2015 Acta Phys. Sin. 64 094302 (in Chinese) [夏峙, 李秀坤 2015 物理学报 64 094302]
[13]	Li F H, Zhang Y J, Zhang R H, Liu J J 2010 Phys. Sci. China 53 1408
[14]	Zhu N, Wu S 2009 J. Acoust. Soc. Am. 126 2254
[15]	Bouaynaya N, Charif-Chefchaouni M, Schonfeld D 2008 IEEE Trans. Pattern Anal. Mach, Intell. 30 5
[16]	Tang W L, Fan J 2004 Acta Acustica 29 5 (in Chinese) [汤渭霖, 范军 2004 声学学报 29 5]
[17]	Tesei A, Fawcett J A, Lim R 2008 Appl. Acoust. 69 422
[18]	Touraine N, Haumesser L, De’cultot D, Maze G 2000 J. Acoustic Soc. Am. 108 5
[19]	Tang W L 1994 Acta Acustica 19 92 (in Chinese) [汤渭霖 1994 声学学报 19 92]
[20]	Thomas M, Lethakumary B, Jacob R 2012 ICCEET p717

引用本文:

Citation:

计量

文章访问数: 1229
PDF下载量: 304
被引次数: 0

水下目标声散射信号的时频域盲抽取

1. 哈尔滨工程大学, 水声技术重点实验室, 哈尔滨 150001;

2. 哈尔滨工程大学水声工程学院, 哈尔滨 150001

通信作者: 李秀坤, lixiukun@hrbeu.edu.cn

基金项目:

国家自然科学基金（批准号：51279033）和黑龙江省自然科学基金（批准号：F201346）资助的课题.

收稿日期: 2016-03-15

修回日期: 2016-06-10

刊出日期: 2016-08-05

摘要: 目标声散射机理及其散射特性为识别目标的物理依据. 针对水下目标声散射成分在时-频域存在相互混叠干扰，造成目标弹性声散射特征不稳定的问题，提出一种适合在欠定问题下分离目标声散射成分的时频域盲抽取方法. 研究声散射成分的时频特征差异，构造目标回波单源自项的空间时频分布矩阵，通过对其进行特征值分解抽取相应的声散射成分，建立描述目标声散射物理特性的信号模型. 抽取出的目标各弹性波分量与以表面环绕波产生理论计算结果相符. 仿真与消声水池实验数据处理结果表明，该算法可以分离出目标回波的各个声散射成分，提高了分离信号的输出信噪比，为水下目标识别提供稳定和可靠的特征.

关键词:

Blind source extraction based on time-frequency characteristics for underwater object acoustic scattering

1.
Acoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China;

2.
College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China

Fund Project:

Project supported by the National Natural Science Foundation of China (Grant No. 51279033) and the Natural Science Foundation of Heilongjiang Province, China (Grant No. F201346).

Received Date: 15 March 2016

Accepted Date: 10 June 2016

Published Online: 05 August 2016

Abstract: The physical mechanism and signal characteristics of acoustic scattering are the vital basis for target recognition. But underwater target acoustic scattering components are aliasing in time-frequency (TF) domain, for which the target elastic acoustic scattering characteristics are difficult to detect. Additionally, the existing blind source separation methods are effective only on condition that the number of array elements is equal to or greater than the number of the source signals. To address these problems, a novel TF domain blind source extraction method of separating target acoustic scattering components is proposed in this paper. The method only uses the TF energy characteristic differences among the target acoustic scattering components, and special limitations on target echo structures are unnecessary. Image morphology filter is used to remove the cross-term interference from time-frequency distribution (TFD) of the received array signals. Then, the single source which shows maximum energy concentration at the corresponding auto-term TF points is extracted through three operations: i) selecting the single source auto-term TF points from the auto-term ones; ii) constructing the spatial TFD matrix according to the selected single source auto-term TF points; iii) obtaining the single source by decomposing the eigenvalue of their spatial TFD matrix. Finally, the extracted single signal is excluded by the tightening process from the received array signals, and each single signal is separated successively by repeating the above steps. In addition, a signal processing model which can describe the physical characteristics of the target echoes is established based on the separated signal components. Simulations illustrate that the image morphological filter can remove the cross-term interference and improve the TF resolution of the Wigner-Ville distribution. Anechoic pool experimental results show that the TF domain blind source extraction algorithm can well separate each target acoustic scattering component, it can also achieve a higher output signal-to-noise ratio. Furthermore, the separated elastic acoustic scattering components are in good agreement with the results computed by the surface wave generating theory, so the method can provide the robust and reliable feature for underwater target recognition.

Keywords:

全文HTML

参考文献 (20)

搜索

留言板