2025_programme: Extraction of Green’s function via blind deconvolution using iterative adaptive approach for small horizontal arrays

• Day: June 17, Tuesday
    Location / Time: D. CHLOE at 18:20-18:40
• Last minutes changes: -
• Session: 06. Enhancing underwater acoustic sensing through machine learning
  Organiser(s): Cheng Chi
  Chairperson(s): Peng Xiao
• Lecture: Extraction of Green’s function via blind deconvolution using iterative adaptive approach for small horizontal arrays
  Paper ID: 2326
  Author(s): Wei Shao, Yujie Wang, Guanqun Wang, Cheng Chi, Yu Li, Haining Huang
  Presenter: Wei Shao
  Abstract: Ray-based blind deconvolution (RBD) has been proposed as a popular technique for extracting the Green's function in underwater acoustic channels. However, the conventional RBD depends on large arrays with sufficient spatial resolution. For small horizontal arrays, the conventional RBD deteriorates seriously. The reason is that the poor spatial resolution capability of the small arrays induces severe energy leakage and sidelobes when using the conventional method. This paper proposes an iterative-adaptive-approach-based (IAA) method that overcomes the spatial resolution shortcoming when using small horizontal arrays to extract the Green’s function. Both simulation and experiment demonstrate the superior performance of the IAA-based method in suppressing energy leakage and sidelobes in the Green's function extraction for small horizontal arrays.
• Corresponding author: Mr Wei Shao
  Affiliation: Institute of Acoustics, Chinese Academy of Sciences, Beijing, China
  Country: China