Fast raypath separation based on low-rank matrix approximation in a shallow-water waveguide

Longyu Jiang (1) , Wenbo Song (1) , Zhe Zhang (1) , Chunfeng Yang (1, 2) , Shijie Wang (1) , Philippe Roux (3)

1 Southeast univ.
2 CRIBS - Centre de Recherche en Information Biomédicale sino-français
3 ISTerre - Institut des Sciences de la Terre

Subspace algorithms based on higher-order cumulants were developed to achieve high-resolution separation in non-Gaussian processes. However, singular value decomposition (SVD) of a huge matrix is an unavoidable step of these algorithms. The memory space and running time required by the decomposition are super-linear with respect to the size of the matrix, which is prohibitive in terms of practical applications. Thus, in this paper, a fast raypath separation algorithm based on low-rank matrix approximation is proposed in a shallow-water waveguide. The experimental results illustrate that the proposed algorithm dramatically reduces the consumption of time and space, with arbitrarily small error, compared to conventional higher-order cumulant-based algorithms. (C) 2018 Acoustical Society of America

Domains: Life Sciences [q-bio]; Bioengineering

Longyu Jiang, Wenbo Song, Zhe Zhang, Chunfeng Yang, Shijie Wang, et al.. Fast raypath separation based on low-rank matrix approximation in a shallow-water waveguide. Journal of the Acoustical Society of America, 2018, 143 (4), pp.EL271-EL277. ⟨10.1121/1.5030916⟩. ⟨hal-01807117⟩