Abstract
We approximate the underwater acoustic wave problem for locating sources in that medium. We create a time dependent synthetic data-set of sensor recorded pressures, based on a small set of sensors placed in the domain, and perturb this data with high random multiplicative noise. We show that reference time-reversal based method struggles with high noise, and a naive deep-learning method also fails. We propose a method, based on physically-informed neural-networks and time-reversal, for approximating the source location even in the presence of high sensors noise.
Original language | English |
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Article number | 111592 |
Journal | Journal of Computational Physics |
Volume | 470 |
DOIs | |
State | Published - 1 Dec 2022 |
Keywords
- Inverse problems
- Learning
- Physically-informed
- Sensors
- Time-reversal