Dispersive Grid-free Orthogonal Matching Pursuit for Modal Estimation in Ocean Acoustics

Thomas Paviet-Salomon (1) , Clément Dorffer (1) , Julien Bonnel (1) , Barbara Nicolas (2) , Thierry Chonavel (3, 4) , Angélique Drémeau (5)

1 Lab-STICC_ENSTAB_CID_TOMS
2 Imagerie Ultrasonore
3 Lab-STICC_IMTA_CID_TOMS
4 IMT Atlantique - SC - Département Signal et Communications
5 Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance

Considering low-frequency acoustic sources, shallow-water environments act as modal dispersive waveguides. In this context, the signal can be described as a sum of a few modal components, each of them propagating with its own wavenumber. When dealing with broadband sources, wavenumber-frequency (f-k) diagrams constitute popular representations naturally enabling modal separation. Based on a Fourier transform, they require however a large number of sensors to resolve wavenumbers with a high-resolution. This limitation can be overcame by adding some physical priors to the processing method. In the continuation of previous works, we propose here a new grid-free algorithm allowing a super-resolution of the (f-k) diagram by benifiting from the sparse nature of the wavenumber spectrum and embedding the broadband behavior of the wavenumbers within the algorithm. The method is validated on simulated data.

Mots clés: Index Terms-Wavenumbers estimation; greedy algorithms; grid-free algorithms; sparse repre- sentation; Index Terms-Wavenumbers estimation

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Thomas Paviet-Salomon, Clément Dorffer, Julien Bonnel, Barbara Nicolas, Thierry Chonavel, et al.. Dispersive Grid-free Orthogonal Matching Pursuit for Modal Estimation in Ocean Acoustics. ICASSP 2020 : IEEE International Conference on Acoustics, Speech and Signal Processing, May 2020, Barcelona, Spain. pp.4602-4606, ⟨10.1109/ICASSP40776.2020.9054365⟩. ⟨hal-02902490v2⟩