In underwater acoustic localization via matched-field-processing, given a propagation model and a suitable environmental parameterization, one searches for the location (of the transmitter or receiver) whose replica field is closest to the observed one. The high computational complexity of such non-gradient-based optimization methods renders them infeasible for many real-time scenarios, especially when an accurate solution is desired, due to resolution of the search grid required, or as the search dimensionality increases (e.g., when it is necessary to optimize over uncertain environmental parameters such as sound speed or bathymetry). In this work, we propose a ray-based, differentiable model for acoustic propagation for the purpose of a gradient-based optimization for localization. For localization applications in which accurate times of arrivals might not be available, the proposed method can be adapted to work without requiring this information. In such a scenario, it seeks the location (and possibly environmental parameters) that minimize the squared-error between the observed signal and its estimate via the differentiable model. We leverage the PyTorch optimization and auto-differentiation tools for the implementation and demonstrate successful localization on synthetic data inspired from a real-world scenario in a dense multipath environment.
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8 May 2022
184th Meeting of the Acoustical Society of America
8–12 May 2023
Chicago, Illinois
Computational Acoustics: Paper 2pSP11
September 18 2023
A gradient-based optimization approach for underwater acoustic source localization
Dariush Kari;
Dariush Kari
1
Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign
, Urbana, IL, 61801, USA
; dkari2@illinois.edu; acsinger@illinois.edu
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Andrew C. Singer
;
Andrew C. Singer
1
Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign
, Urbana, IL, 61801, USA
; dkari2@illinois.edu; acsinger@illinois.edu
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Hari Vishnu
;
Hari Vishnu
2
Acoustic Research Laboratory, National University of Singapore
, Singapore, SINGAPORE
; harivishnu@gmail.com
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Amir Weiss
Amir Weiss
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Proc. Mtgs. Acoust. 51, 022002 (2023)
Article history
Received:
June 08 2023
Accepted:
June 27 2023
Connected Content
This is a companion to:
Underwater acoustic localization via gradient-based optimization
Citation
Dariush Kari, Andrew C. Singer, Hari Vishnu, Amir Weiss; A gradient-based optimization approach for underwater acoustic source localization. Proc. Mtgs. Acoust. 8 May 2023; 51 (1): 022002. https://doi.org/10.1121/2.0001753
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