Gaussian mixture model fitting and suppression of towed array flow noise

被引:0
作者
Wang, Ran [1 ]
Wang, Guangzhe [1 ]
Zhang, Chenyu [2 ]
Guo, Qixin [3 ]
Zhang, Yongli [1 ]
Yu, Liang [4 ]
Gao, Yuan [5 ,6 ]
Chen, Nuo [5 ,6 ]
机构
[1] School of Logistics Engineering, Shanghai Maritime University, Shanghai
[2] College of Power and Energy Engineering, Harbin Engineering University, Harbin
[3] College of Electronic and Information Engineering, Tongji University, Shanghai
[4] School of Civil Aviation, Northwestern Polytechnical University, Xi’an
[5] Shanghai Marine Electronic Equipment Research Institute, Shanghai
[6] Science and Technology on Underwater Acoustics Antagonizing Laboratory, Shanghai
来源
Shengxue Xuebao/Acta Acustica | 2024年 / 49卷 / 05期
关键词
Expectation maximum algorithm; Flow noise; Gaussian mixture model; Sonar detection; Towed array;
D O I
10.12395/0371-0025.2023033
中图分类号
学科分类号
摘要
Aiming at the problem that it is difficult to accurately model and suppress the towed array flow noise caused by the pressure fluctuation in the turbulent boundary layer, this paper analyzes the generation mechanism of the towed array flow noise and the statistical properties of the noise. A hybrid Gaussian model modelling method is developed for the non-Gaussian distributed towed array flow noise, and a low-rank model of the acoustic source signal in the multi-channel towed array is established. The parameters in the model of the flow noise and the acoustic source signal are solved by the expectation-maximization algorithm, which ultimately realizes the separation of the flow noise and acoustic source signal in the received signal of the hydrophone. The results of the flow noise suppression and target orientation estimation of the actual lake test data show that the maximum side-valve level suppression reaches 8−10 dB without affecting the localization results. © 2024 Science Press. All rights reserved.
引用
收藏
页码:1030 / 1040
页数:10
相关论文
共 50 条
[1]   Numerical prediction of flow noise levels on towed sonar array [J].
Karthik, K. ;
Jeyakumar, S. ;
Sebastin, J. Sarathkumar .
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART M-JOURNAL OF ENGINEERING FOR THE MARITIME ENVIRONMENT, 2021, 235 (02) :600-606
[2]   FITTING A GAUSSIAN MIXTURE MODEL THROUGH THE GINI INDEX [J].
Lopez-Lobato, Adriana Laura ;
Avendano-Garrido, Martha Lorena .
INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE, 2021, 31 (03) :487-500
[3]   FLOW NOISE MEASUREMENT OF SURFACE SHIP WITH TOWED MODEL [J].
GAO Xiaopeng School of Naval Architecture Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai China BI Yi College of Naval Architecture and Power Naval University of Engineering Wuhan China MIAO Guoping School of Naval Architecture Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai China .
Journal of Hydrodynamics, 2008, 20 (06) :784-789
[4]   Flow Noise Measurement of Surface Ship with Towed Model [J].
Xiao-peng Gao ;
Yi Bi ;
Guo-ping Miao .
Journal of Hydrodynamics, 2008, 20 :784-789
[5]   FLOW NOISE MEASUREMENT OF SURFACE SHIP WITH TOWED MODEL [J].
Gao Xiao-peng ;
Bi Yi ;
Miao Guo-ping .
JOURNAL OF HYDRODYNAMICS, 2008, 20 (06) :784-789
[6]   Multiresolution Based Gaussian Mixture Model for Background Suppression [J].
Mukherjee, Dibyendu ;
Wu, Q. M. Jonathan ;
Thanh Minh Nguyen .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2013, 22 (12) :5022-5035
[7]   PARTICLE FLOW PARTICLE FILTER FOR GAUSSIAN MIXTURE NOISE MODELS [J].
Pal, Soumyasundar ;
Coates, Mark .
2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2018, :4249-4253
[8]   Gaussian mixture model fitting method for uncertainty quantification by conditioning to production data [J].
Gao, Guohua ;
Jiang, Hao ;
Vink, Jeroen C. ;
Chen, Chaohui ;
El Khamra, Yaakoub ;
Ita, Joel J. .
COMPUTATIONAL GEOSCIENCES, 2020, 24 (02) :663-681
[9]   Gaussian mixture model fitting method for uncertainty quantification by conditioning to production data [J].
Guohua Gao ;
Hao Jiang ;
Jeroen C. Vink ;
Chaohui Chen ;
Yaakoub El Khamra ;
Joel J. Ita .
Computational Geosciences, 2020, 24 :663-681
[10]   Adaptive Riemannian stochastic gradient descent and reparameterization for Gaussian mixture model fitting [J].
Ji, Chunlin ;
Fu, Yuhao ;
He, Ping .
ASIAN CONFERENCE ON MACHINE LEARNING, VOL 222, 2023, 222