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The normal modes cannot be extracted even in the Pekeris waveguide when the source-receiver distance is very close. This paper introduces a normal mode extraction method based on a dedispersion transform (DDT) to solve this problem. The method presented here takes advantage of DDT, which is based on the waveguide invariant such that the dispersion associated with all of the normal modes is removed at the same time. After performing DDT on a signal received in the Pekeris waveguide, the waveform of resulting normal modes is very close to the source signal, each with different position and amplitude. Each normal mode can be extracted by determining its position and amplitude parameters by applying particle swarm optimization (PSO). The waveform of the extracted normal mode is simply the waveform of the source signal; the real waveform of the received normal mode can then be recovered by applying dispersion compensation to the source signal. The method presented needs only one receiver and is verified with experimental data.
Czasopismo
Rocznik
Tom
Strony
11--18
Opis fizyczny
Bibliogr. 19 poz., rys., wykr.
Twórcy
autor
- South China Sea Institute of Oceanology, Chinese Academy of Sciences, 164, West Xingang Road, Guangzhou 510301, Guangdong Prov., P. R. China
- University of Chinese Academy of Sciences, 19A, Yuquan Road, Beijing 100049, P. R. China
- Key Laboratory of Marine Science and Numerical Modeling, The First Institute of Oceanography, State Oceanic Administration, 6, Xianxialing Road, Qingdao 266061, Shandong Prov., P. R. China
autor
- Key Laboratory of Marine Science and Numerical Modeling, The First Institute of Oceanography, State Oceanic Administration, 6, Xianxialing Road, Qingdao 266061, Shandong Prov., P. R. China
autor
- College of Information Science and Technology, Ocean University of China, 238, Songling Road, Qingdao 266100, Shandong Prov., P. R. China
autor
- Key Laboratory of Marine Science and Numerical Modeling, The First Institute of Oceanography, State Oceanic Administration, 6, Xianxialing Road, Qingdao 266061, Shandong Prov., P. R. China
autor
- Key Laboratory of Marine Science and Numerical Modeling, The First Institute of Oceanography, State Oceanic Administration, 6, Xianxialing Road, Qingdao 266061, Shand
Bibliografia
- 1. Bonnel J., Nicolas B., Mars J.I., Walker S.C. (2010), Estimation of modal group velocities with a single receiver for geoacoustic inversion in shallow water, Journal of the Acoustical Society of America, 128, 2, 719–727.
- 2. Bonnel J., Gervaise C., Roux P., Nicolas B., Mars J.I. (2011), Modal depth function estimation using time-frequency analysis, Journal of the Acoustical Society of America, 130, 1, 61–71.
- 3. Bonnel J., Gervaise C., Nicolas B., Mars J.I. (2012), Single-receiver geoacoustic inversion using modal reversal, Journal of the Acoustical Society of America, 131, 1, 119–128.
- 4. Daubechies I., Lu J., Wu H. (2011), Synchrosqueezed wavelet transforms: an empirical mode decompositionlike tool, Applied and Computational Harmonic Analysis, 30, 2, 243–261.
- 5. Francois R.E., Garrison G.R. (1982), Sound absorption based on ocean measurements. Part II: Boricacid contribution and equation for total absorption, Journal of the Acoustical Society of America, 72, 6, 1879–1890.
- 6. Gao D.Z., Wang N., Wang H.Z. (2010), A Dedispersion Transform for Sound Propagation in Shallow Water Waveguide, Journal of Computational Acoustics, 18, 3, 245–257.
- 7. Grelowska G., Kozaczka E., Kozaczka S., Szymczak W. (2013), Underwater noise generated by a small ship in the shallow sea, Archives of Acoustics, 38, 3, 351–356.
- 8. Huang N.E., Shen Z., Long S.R., Wu M.C., Shih H.H., Zheng Q., Yen N., Tung C.C., Liu H.H. (1998), The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 454, 1971, 903–995.
- 9. Jensen F.B., Kuperman W.A., Porter M.B., Schmidt H. (2011), Computational ocean acoustics, Springer, New York.
- 10. Kennedy J., Eberhart R. (1995), Particle swarm optimization, Proceedings of IEEE International Conference on Neural Networks, pp. 1942–1948, Perth.
- 11. Makar A. (2004), Estimation of the time delay of hydroacoustic signals for passive location of underwater objects, Archives of Acoustics, 29, 3, 435–445.
- 12. Neilsen T.B., Westwood E.K., Udagawa T. (1997), Mode function extraction from a VLA using singular value decomposition, Journal of the Acoustical Society of America, 101, 5, 3025.
- 13. Neilsen T.B., Westwood E.K. (2002), Extraction of acoustic normal mode depth functions using vertical line array data, Journal of the Acoustical Society of America, 111, 2, 748–756
- 14. Nicolas B., Mars J.I., Lacoume J. (2006), Source depth estimation using a horizontal array by matchedmode processing in the frequency-wavenumber domain, EURASIP Journal on Applied Signal Processing, 2006, 65901, 1–16.
- 15. Rilling G., Flandrin P. (2008), One or two frequencies? The empirical mode decomposition answers, IEEE Transactions on Signal Processing, 56, 1, 85–95.
- 16. Walker S.C., Roux P., Kuperman W.A. (2005), Data-based mode extraction with a partial water column spanning array, Journal of the Acoustical Society of America, 118, 3, 1518–1525.
- 17. Wu H., Flandrin P., Daubechies I. (2011), One or two frequencies? The synchrosqueezinganswers, Advances in Adaptive Data Analysis, 3, 01&02, 29–39.
- 18. Zhao D., Huang Z., Su S., Li T. (2013), Matched-eld source localization with a mobile short horizontal linear array in offshore shallow water, Archives of Acoustics, 38, 1, 105–113.
- 19. Zhao Z., Wang N., Gao D., Wang H. (2010), Broadband source ranging in shallow water using the Ω-interference spectrum, Chinese Physics Letters, 27, 6, 064301
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-cbcadd67-0c0e-491f-bb49-289f5689d1ca
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