

FOLLOWUS
1. National Laboratory of Acoustics Institute of Acoustics Chinese Academy of Sciences
2. Haikou Laboratory of Acoustics Institute of Acoustics Chinese Academy of Sciences
3. Graduate School Chinese Academy of Sciences
网络首发:2010-09-11,
纸质出版:2010
Scan QR Code
Matched-field inversion of sound speed profile in shallow water using a parallel genetic algorithm[J]. 海洋湖沼学报(英文), 2010,28(5):1080-1085.
Yu, Y., Li, Z. & He, L. Matched-field inversion of sound speed profile in shallow water using a parallel genetic algorithm., Chin. J. Ocean. Limnol. 28, 1080–1085 (2010). https://doi.org/10.1007/s00343-010-9004-7
Matched-field inversion of sound speed profile in shallow water using a parallel genetic algorithm[J]. 海洋湖沼学报(英文), 2010,28(5):1080-1085. DOI: 10.1007/s00343-010-9004-7.
Yu, Y., Li, Z. & He, L. Matched-field inversion of sound speed profile in shallow water using a parallel genetic algorithm., Chin. J. Ocean. Limnol. 28, 1080–1085 (2010). https://doi.org/10.1007/s00343-010-9004-7 DOI:
A sound speed profile plays an important role in shallow water sound propagation. Concurrent with in-situ measurements
many inversion methods
such as matched-field inversion
have been put forward to invert the sound speed profile from acoustic signals. However
the time cost of matched-field inversion may be very high in replica field calculations. We studied the feasibility and robustness of an acoustic tomography scheme with matched-field processing in shallow water
and described the sound speed profile by empirical orthogonal functions. We analyzed the acoustic signals from a vertical line array in ASIAEX2001 in the East China Sea to invert sound speed profiles with estimated empirical orthogonal functions and a parallel genetic algorithm to speed up the inversion. The results show that the inverted sound speed profiles are in good agreement with conductivity-temperature-depth measurements. Moreover
a posteriori probability analysis is carried out to verify the inversion results.
Banzhaf W, Nordin P, Keller R E et al. 1998. Genetic Programming—An Introduction. Morgan Kaufmann, San Francisco, CA.
Dosso S E. 2002. Quantifying uncertainty in geoacoustic inversion. I. A fast Gibbs sampler approach. J. Acoust. Soc. Am., 111(1): 129–142.
Goldberg, D E. 1989. Genetic Algorithms in Search, Optimization and Machine Learning. Kluwer Academic Publishers, Boston, MA.
Gerstoft P. 1993. Inversion of seismoacoustic data using genetic algorithms and a posteriori probability distributions. J. Acoust. Soc. Am., 95(2): 770–782.
Gerstoft P, Mecklenbräuker C F. 1998. Ocean acoustic inversion with estimation of a posteriori probability distributions. J. Acoust. Soc. Am., 104(2): 808–819.
He L, Li Z L, Zhang R H et al. 2006. Sound velocity profile of the East China Sea expression by EOF and inversion by MFP. Progress in Natural Science, 3(16): 351–355. (in Chinese)
LeBlanc L R, Middleton F H. 1980. An underwater acoustic sound velocity data model. J. Acoust. Soc. Am., 67(6): 2 055–2 062.
Li Z L, Zhang R H, Yan J et al. 2004. Geoacoustic inversion by matched-field processing combined with the vertical reflection coefficients and vertical correlation. IEEE J. Ocean. Eng., 29(4): 973–979.
Sambridge M. 1999. Geophysical inversion with a neighbourhood algorithm I. Searching a parameter space. Geophys. J. Int., 138: 479–494.
Shen Y H, Ma Y L, Tu Q P. 2000. On expression of ocean sound profile by layered empirical orthogonal function (EOF). Journal of Northwestern Polytechnical University, 18(1): 90–93. (in Chinese with English abstract)
Taroudakis M I, Markaki M G. 1997. On the use of matched-field processing and hybrid algorithm for vertical slice tomography. J. Acoust. Soc. Am., 102(2): 885–895.
Tolstoy A, Diachok O, Frazer L N. 1991. Acoustic tomography via match field processing. J. Acoust. Soc. Am., 89(3): 1 119–1 127.
Westwood E K. 1992. Broadband matched-field source localization. J. Acoust. Soc. Am., 91(5): 2 777–2 789.
0
浏览量
0
Downloads
6
CSCD
关联资源
相关文章
相关作者
相关机构

京公网安备11010802024621