@inproceedings{197397c5335b42348624bdd266ff047d,
title = "Wall Localization in a Water Tank Using a Cooperative Source of Opportunity",
abstract = "Model-based underwater acoustic localization in confined spaces like water tanks typically depend on the geometry. This paper investigates the problem of water tank wall localization using an acoustic source of opportunity that may not offer sufficient bandwidth for time-of-arrival-based methods to perform satisfactorily. We propose that in these scenarios, approximate time-of-arrival-based methods are used followed by a ray-based differentiable model using a gradient-based optimization to obtain a more accurate estimate. We demon-strate the successful operation of the algorithm on data ob-tained from a tank simulator, whose parameters are adjusted to those of the Scripps Ocean Atmosphere Research Simula-tor (SOARS).",
keywords = "gradient descent, nonconvex optimization, source of opportunity, underwater acoustic localization",
author = "Dariush Kari and Singer, {Andrew C.}",
note = "This work has been supported by the Office of Naval Research (ONR) under grant N00014-19-1-2662.; 2024 IEEE Conference on Computational Imaging Using Synthetic Apertures, CISA 2024 ; Conference date: 20-05-2024 Through 23-05-2024",
year = "2024",
doi = "10.1109/CISA60639.2024.10576258",
language = "English (US)",
series = "2024 IEEE Conference on Computational Imaging Using Synthetic Apertures, CISA 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2024 IEEE Conference on Computational Imaging Using Synthetic Apertures, CISA 2024",
address = "United States",
}