The Discussion of Acoustic Seabed Sediment Classification Methods

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Acoustic seabed sediment classification method is always important research contents in marine geology and marine acoustics because of its characters of low-cost and high efficiency. At present, there are mainly three types of acoustic seabed sediment classification methods:(1) the echo signal statistical characteristics classification; (2) image texture classification; (3) submarine acoustic parameter inversion method. The principles of anterior two classification methods are similar, which is based on statistics, unknown sediment type can be concluded according to the statistical characteristics of known sediment. There are many usable acoustic equipments and commercial classification software for the two kinds of methods. The third type method is based on suitable seabed sediment model. Seabed acoustic characteristic parameters are inversed and thus seabed sediment can be classified. At present, there are few usable acoustic equipment and commercial classification software for the third method, but it's more accurate than the anterior two classification methods.

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1811-1816

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November 2012

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] B.LU, G.X. LI. Submarine sediment acoustic field measurement and sampling systems.Ocean Technology(In Chinese), Vol.19(2000) No.3, pp.31-33

Google Scholar

[2] A Barbagelata, M D Richardson and B Miaschi, et al. ISSAMS:an in situ sediment acoustic measurement system.Hovem J M. Richardson M D(Eds.). Shear Waves in Marine Sediments .Kluwer Academic Publishers, Dordrecht, (1991),3 pp.305-312

DOI: 10.1007/978-94-011-3568-9_34

Google Scholar

[3] L.R Breslau.. Classification of Sea-Floor Sedimnets with a Shipborne Acoustical System. Le Petrole et La Mer, Vol.132(1965), pp.1-9

Google Scholar

[4] D.T. Smith, W. N.LI Echo-Sounding and Seafloor Sediments. Marine Geology. Vol.4(1996), pp.353-364

Google Scholar

[5] F.L.PAN, B.LU and S.J.HUANG. Possibility of sediment classification with acoustic technology. South China Sea Institute of Oceanology, CAS. The Sound and Light Field Research Papers in Nansha Sea-area[C ]. Beijing: Science Press,(1996)

Google Scholar

[6] J.S.MENG and D.H.GUAN. Incident pulse method to estimate sea surface sediment attenuation coefficient. Acta Oceanologica Sinica(In Chinese), Vol.6(1984) No.6, pp.867-873

Google Scholar

[7] H.Q.ZHANG and N. WANG. Seabed Classification Using Grey Level Profiling Images. Periodical of Ocean University of China(In Chinese), Vol.36(2006) No.(Sup.2), pp.131-135

Google Scholar

[8] F.B.GUO and D.W.DU. Characteristic Analysis of Bathymetric Data for Different Types of Bottom Material. Advances in Marine Science(In Chinese), Vol.21(2003) No.3, pp.349-354

Google Scholar

[9] C.H.TAO, X.L.JIN and F.XU et al. The prospect of seabed classification technology. Donghai Marine Science(In Chinese), Vol.22(2004) No.3, pp.28-33

Google Scholar

[10] H. J. Kim, J. K. Chang and H. T. Jou, et al. Seabed classification from acoustic profiling data using the similarity index. J. Acoust. Soc. Am, Vol.111(2002) No.2, pp.794-799

DOI: 10.1121/1.1433812

Google Scholar

[11] S. T. Alexander, T. C. William and P. Bradley. Acoustic Seabed Classification and Correlation Analysis of Sediment properties by QTC VIEW. Proceeding Oceans 1997 MTS/IEEE, Halifax, Canada.(1997)

DOI: 10.1109/oceans.1997.624114

Google Scholar

[12] S. D. Milligan, L. R. LeBlanc, F. H. Middleton. Statistical grouping of acoustic reflection profiles. J. Acoust. Soc. Am, Vol.64(1978), p.795–807

DOI: 10.1121/1.382045

Google Scholar

[13] W.Y. JI, Y.J.LIN and S.Y.ZHANG. Research on pattern recognition of acoustic sea-bed profiling records and sea-bed geological classification.ACTA ACUSTICA(In Chinese), Vol.26(2001) No.4, pp.365-371

Google Scholar

[14] N. Pican, E. Trucco and M. Ross et al. Texture analysis for seabed classification: Co-occurrence matrices vs self-organizing maps.Proceedings of IEEE/OES OCEANS'98 conference, France:OCEAN, IEEE/OES, CONFERENCE, ORGAN1Z1NG, COMM1TTEE.(1998)

DOI: 10.1109/oceans.1998.725781

Google Scholar

[15] C. G. Rafael and E. W. Richard. Digital Image Processing(Second Edition) . Publishing House of Electronics Industry, Vol.7(2002), pp.666-668

Google Scholar

[16] M. A. Biot. Theory of Propagation of Elastic Waves in a Fluid-Saturated Porous Solid.II. Higher Frequency Range. The Acoustical Society of America Vol.28(1956a) No.2, pp.179-191

DOI: 10.1121/1.1908241

Google Scholar

[17] M. A. Biot.. Theory of Propagation of Elastic Waves in a Fluid-Saturated Porous Solid.I. Low-Frequency Range. The Acoustical Society of America. 28(1956b) No.2, pp.168-178

DOI: 10.1121/1.1908239

Google Scholar

[18] R. D. Stoll. Acoustic Waves in Ocean Sediments. Geophysics. Vol.42(1977) No.4, p.11

Google Scholar

[19] S. G. Schock. A Method for Estimating the Physical and Acoustic Properties of the Sea Bed Using Chirp Sonar Data. Journal of Oceanic Engeering. Vol.29(2004a) No.4, pp.1200-1217

DOI: 10.1109/joe.2004.841421

Google Scholar

[20] S. G. Schock. Remote Estimates of Physical and Acoustic Sediment Properties in the South China Sea Using Chirp Sonar Data and the Biot Model. Journal of Oceanic Engeering. Vol.29(2004b) No.4, pp.1218-1230

DOI: 10.1109/joe.2004.842253

Google Scholar