Blind source separation based on time–frequency morphological characteristics for rigid acoustic scattering by underwater objects

Yang Yang , Xiukun Li

Journal of Marine Science and Application ›› 2016, Vol. 15 ›› Issue (2) : 201 -207.

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Journal of Marine Science and Application ›› 2016, Vol. 15 ›› Issue (2) : 201 -207. DOI: 10.1007/s11804-016-1352-z
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Blind source separation based on time–frequency morphological characteristics for rigid acoustic scattering by underwater objects

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Abstract

Separation of the components of rigid acoustic scattering by underwater objects is essential in obtaining the structural characteristics of such objects. To overcome the problem of rigid structures appearing to have the same spectral structure in the time domain, time–frequency Blind Source Separation (BSS) can be used in combination with image morphology to separate the rigid scattering components of different objects. Based on a highlight model, the separation of the rigid scattering structure of objects with time–frequency distribution is deduced. Using a morphological filter, different characteristics in a Wigner–Ville Distribution (WVD) observed for single auto term and cross terms can be simplified to remove any cross-term interference. By selecting time and frequency points of the auto terms signal, the accuracy of BSS can be improved. An experimental simulation has been used, with changes in the pulse width of the transmitted signal, the relative amplitude and the time delay parameter, in order to analyzing the feasibility of this new method. Simulation results show that the new method is not only able to separate rigid scattering components, but can also separate the components when elastic scattering and rigid scattering exist at the same time. Experimental results confirm that the new method can be used in separating the rigid scattering structure of underwater objects.

Keywords

underwater object / highlight structure / rigid scattering components / image morphology / time–frequency blind source separation

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Yang Yang, Xiukun Li. Blind source separation based on time–frequency morphological characteristics for rigid acoustic scattering by underwater objects. Journal of Marine Science and Application, 2016, 15(2): 201-207 DOI:10.1007/s11804-016-1352-z

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References

[1]

Belouchrani A, Amin MG. Blind source separation based on time–frequency signal representations. IEEE Transactions on Signal Processing, 1998, 46(11): 2888-2897

[2]

Bouaynaya N, Charif-Chefchaouni M, Schonfeld D. Theoretical foundations of spatially variant mathematical morphology part I: Binary images. IEEE Transactions on Pattern Analysis and Machine Intellgence, 2008, 30(5): 823-836

[3]

Holobar A, Fevotte C, Doncarli C, Damjan Z. Single autoterms selection for blind source separation in time-frequency plane, 2002

[4]

Kamran ZM, Leyman AR, Merain K. Techniques for blind source separation using higher-order statistics. Proceedings of the Tenth IEEE Work shop on Statistical Signal and Array Processing, 2000, 334-338

[5]

La Follett JR, Williams KL, Marston PL. Boundary effects on backscattering by a solid aluminum cylinder: Experiment and finite element model comparisons. Journal of the Acoustical Society of America, 2011, 43(30): 669-672

[6]

Li FH, Zhang YJ, Zhang RH, Liu JJ. Interference structure of shallow water reverberation in time-frequency distribution. Science China (Physics, Mechanics and Astronomy), 2010, 53(8): 1408-1411

[7]

Li R, Ma Y, Yang K. Blind estimation of shallow water acoustic channel. Acta Acoustica, 2007, 32(1): 10-18

[8]

Li X, Meng X, Xia Z. Characteristics of the geometrical scattering waves from underwater target in fractional Fourier transform domain. Acta Physica Sinica, 2015, 64(6): 064302-1

[9]

Li X, Xia Z. Research of underwater bottom object and reverberation in feature space. Journal of Marine Science and Application, 2013, 12(2): 235-239

[10]

Li X, Xia Z. Separation of elastic acoustic scattering of underwater object. Acta Physica Sinica, 2015, 64(9): 094302-1

[11]

Liu Y, Liu C, Zhao Y, Zhu J. A blind beamforming algorithm for multitarget signals based on time-frequency analysis. Acta Physica Sinica, 2015, 64(11): 114302-1

[12]

Ma Ming, Shen Yuehong, Niu Yingtao, Kong Zhaoyu, 2007). Performance of blind source separation based on spatial time-frequency distribution for non-stationary signals. 29(3), 56–60.

[13]

Pan A, Fan J, Wang B. Acoustic scattering from a double periodically bulk headed and ribbed finite cylindrical shell. Journal of the Acoustical Society of America, 2013, 134(5): 3452-3463

[14]

Pan A, Zhuo L, Fan J. Research on the echo characteristic of underwater small targets. Journal of Shanghai Jiao Tong University, 2012, 46(7): 1163-1167

[15]

Plotnick S, Marston PL, Williams KL. High frequency backscattering by a solid cylinder with axis tilted relative to a nearby horizontal surface. Journal of the Acoustical Society of America, 2015, 137(1): 470-480

[16]

Tang W. The highlight model of sonar object echo. Acta Acustica, 1994, 19(2): 92-99

[17]

Thomas M, Lethakumary B, Jacob R. Performance comparison of multi-component signals using WVD and Cohen’s class variants. 2012 International Conference on Computing, Electronics and Electrical Technologies (ICCEET), 2012, 717-722

[18]

Zhang J, Papandreou-Suppappola A, Gottin B, Ioana C. Time-frequency characterization and receiver waveform design for shallow water environments. IEEE Transactions on Signal Processing, 2009, 57(8): 2973-2985

[19]

Zhu N, Wu S. Extraction of acoustic signals using blind source separation method. Journal of the Acoustical Society of America, 2009, 126: 2254

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