2025_programme: Research on the Inversion Method of Deep-Sea Hydrographic Environmental Parameters Using Towed Line Arrays

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  • Day: June 19, Thursday
      Location / Time: TBA at 15:30 - 16:30
  • Last minutes changes: -
  • Session: Poster session
    Organiser(s): N/A
    Chairperson(s): N/A
  • Lecture: Research on the Inversion Method of Deep-Sea Hydrographic Environmental Parameters Using Towed Line Arrays
    Paper ID: 2147
    Author(s): bo yuan, licheng lu, guoli song, fujin yang, pengxi zhou, li ma
    Presenter: Bo Yuan
    Abstract: In response to the demand for real-time acquisition of hydrographic environmental parameters for deep-sea underwater target detection, positioning, and communication navigation, this study conducts an inversion analysis based on data from a towed line array. Traditional methods for inverting hydrographic parameters typically rely on vertical arrays, which have limited mobility and can only obtain parameters from local areas. In contrast, the towed line array enables a survey-style acquisition of hydrographic parameters, allowing for the collection of a large amount of hydrographic data in a short period and at a low cost. Previously, survey-style methods for obtaining hydrographic parameters often depended on expendable temperature-depth profilers, which have significant drawbacks in temporal and spatial resolution and are also cost-prohibitive. This study utilizes the delay time difference between the ship-towed active acoustic source and the horizontal line array, correlating it with the sound speed profile, and combines historical hydrographic data to perform inversion using the coefficients of Empirical Orthogonal Functions (EOF). Validation with measured hydrographic data from a specific sea area shows that the average inversion error is within 2 m/s. This method provides an effective solution for real-time algorithms of deep-sea sound speed profiles and the perception of hydrographic environmental parameters in unknown deep-sea areas.
  • Corresponding author: Dr bo yuan
    Affiliation: 19937784647
    Country: China

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