Inverse source problems are central to many applications in acoustics, geophysics, non-destructive testing, and more. Traditional imaging methods suffer from the resolution limit, preventing distinction of sources separated by less than the emitted wavelength. In this work we propose a method based on physically informed neural-networks for solving the source refocusing problem, constructing a novel loss term which promotes super-resolving capabilities of the network and is based on the physics of wave propagation. We demonstrate the approach in the setup of imaging an a priori unknown number of point sources in a two-dimensional rectangular waveguide from measurements of wavefield recordings along a vertical cross section. The results show the ability of the method to approximate the locations of sources with high accuracy, even when placed close to each other.
Skip Nav Destination
Article navigation
October 2023
October 24 2023
A physically informed deep-learning approach for locating sources in a waveguide
Adar Kahana
;
Adar Kahana
a)
Department of Applied Mathematics, Tel Aviv University
, Tel Aviv 69978, Israel
Search for other works by this author on:
Symeon Papadimitropoulos;
Symeon Papadimitropoulos
Department of Applied Mathematics, Tel Aviv University
, Tel Aviv 69978, Israel
Search for other works by this author on:
Eli Turkel;
Eli Turkel
Department of Applied Mathematics, Tel Aviv University
, Tel Aviv 69978, Israel
Search for other works by this author on:
Dmitry Batenkov
Dmitry Batenkov
Department of Applied Mathematics, Tel Aviv University
, Tel Aviv 69978, Israel
Search for other works by this author on:
a)
Email: adarkahana@gmail.com
J. Acoust. Soc. Am. 154, 2553–2563 (2023)
Article history
Received:
March 24 2023
Accepted:
October 05 2023
Citation
Adar Kahana, Symeon Papadimitropoulos, Eli Turkel, Dmitry Batenkov; A physically informed deep-learning approach for locating sources in a waveguide. J. Acoust. Soc. Am. 1 October 2023; 154 (4): 2553–2563. https://doi.org/10.1121/10.0021889
Download citation file:
Sign in
Don't already have an account? Register
Sign In
You could not be signed in. Please check your credentials and make sure you have an active account and try again.
Sign in via your Institution
Sign in via your InstitutionPay-Per-View Access
$40.00
92
Views