Sound-Source Localization in Range-Dependent Shallow-Water Environments Using a Four-Layer Model

Sound-source localization in shallow water is a difficult task due to the complicated environment, e.g., complex sound-speed profile and irregular water bottom reflections. Full-wave numerical techniques are currently able to accurately simulate the propagation of sound waves in such complex environments. However, the source localization problem, which generally involves a large number of sound propagation calculations, still requires a fast computation of the wave equation, and thus a simplified model is well advised. In this paper, a four-layer model is considered, which is able to approximate a wide range of shallow-water environments, particularly those in summer conditions. More specifically, the medium is assumed to be horizontally stratified and vertically divided into four layers, and the sound speed in each layer is assumed to be constant or varying linearly. Under this assumption, the wave propagation can be rapidly computed via a classical wave number integration method. The main contribution of this paper is to show the suitability of the four-layer model in terms of source localization in a complex (range-dependent) environment. The sound-speed profile is assumed to be vertically irregular and horizontally slowly varying and the bottom is nonflat. In the forward problem, sound propagation in complex underwater environments is simulated via a time-domain full-wave simulation approach called the spectral-element method. The source localization error due to model imprecision is analyzed.

Xun Wang, Shahram Khazaie, Dimitri Komatitsch, Pierre Sagaut. Sound-Source Localization in Range-Dependent Shallow-Water Environments Using a Four-Layer Model. IEEE Journal of Oceanic Engineering, 2017, pp.1 - 9. ⟨10.1109/JOE.2017.2775978⟩. ⟨hal-01702364⟩

Journal: IEEE Journal of Oceanic Engineering

Date de publication: 14-12-2017

Auteurs:
  • Xun Wang
  • Shahram Khazaie
  • Dimitri Komatitsch
  • Pierre Sagaut

Digital object identifier (doi): http://dx.doi.org/10.1109/JOE.2017.2775978

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