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Low-frequency Arctic reverberation. II: Modeling of long-range reverberation and comparison with data

混响 散射 声学 航程(航空) 地质学 波导管 北极的 正常模式 物理 光学 材料科学 海洋学 复合材料 振动
作者
T. C. Yang,Thomas J. Hayward
出处
期刊:Journal of the Acoustical Society of America [Acoustical Society of America]
卷期号:93 (5): 2524-2534 被引量:3
标识
DOI:10.1121/1.405829
摘要

In the Arctic ocean, very low-frequency (10–50 Hz) reverberation returns from the ice and bottom both contribute to the total received reverberation and are not easily distinguishable in long-range reverberation data, except where there is a dominant bottom or ice feature. In this paper, a normal-mode model of scattering from surface and bottom protuberances is applied to model long-range reverberation data collected during the CEAREX 89 experiment in the Norwegian/Greenland Seas. Modeled reverberation spectrum levels at 23 Hz are compared with data to investigate the relative contributions of the ice and bottom to the measured reverberation. The normal-mode model of boundary scattering is based on a generalization of recent work of Ingenito [F. Ingenito, J. Acoust. Soc. Am. 82, 2051–2059 (1987)] treating scattering from a rigid sphere in a stratified waveguide. Adiabatic normal mode theory is used to model the propagation to and back from the scatterer in a range-dependent waveguide. Using the small-ka approximation for the scattering functions, where k is the wave number and a is the dimension of the boundary protuberance, the normal-mode calculations of the long-range reverberation levels are found to agree rather well with the CEAREX data for four different measurements involving different bottom bathymetries and source depths. For a source at 91-m depth in the 3000-m-deep basin, it is found that the reverberation level for a receiver at 60 m is dominated by scattering from the ice except for reverberation associated with certain identifiable bottom features. For the same environment but a deeper (244-m) source, reverberation levels from the ice and bottom are more comparable. For a strongly range-dependent environment, returns from bottom features are clearly identifiable in the data.

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