Three-dimensional model benchmarking for cross-slope wedge propagation

Rodríguez, Orlando Camargo; Sturm, Frédéric; Petrov, P. S.; Porter, Michael B.

doi:10.1121/2.0000613

Cited by 6 publications

(1 citation statement)

References 14 publications

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“…This search provides a unique bearing and a new range, which, together with the source depth of the 2D initial guess, represent the center of a reduced neighborhood in which the 3D search can take place. Certainly, there are cases, like cross-slope propagation in a wedge environment [14], for which it is very unlikely to obtain a reliable 2D initial guess. However, the diversity of scenarios for which the 2D initial guess can be obtained is too broad to be considered here; it would be necessary to compare vertical versus horizontal arrays, narrowband versus broadband processing, mild versus rough bathymetries, single versus multiple hydrophone arrays, etc.…”

Section: Introductionmentioning

confidence: 99%

Search Space Reduction for Localization and Tracking of an Acoustic Source

Rodríguez

Zhang

Cheng

2023

Signals

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Experimental data from the SACLANTCEN 1993 Mediterranean Experiment are reviewed to assess the reduction of the search space for the localization and tracking of an acoustic source in a three-dimensional environment. Key to this goal is the availability of an initial estimate of source range and depth (called the 2D initial guess); an ambiguous estimate of source bearing can be obtained from the 2D initial guess through Environmental Signal Processing, and the ambiguity can be removed by searching for the source only in the range/bearing regions where bearing estimates are higher. This search provides a new estimate of source range and a single bearing, which together with the estimate for source depth constitute the center of the reduced search space for source localization and tracking. The suggested approach is tested on experimental data from the SACLANTCEN experiment considering different frequencies, as well as a stationary and a moving source.

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Section: Introductionmentioning

confidence: 99%

Search Space Reduction for Localization and Tracking of an Acoustic Source

Rodríguez

Zhang

Cheng

2023

Signals

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Numerical Enhancements and Parallel GPU Implementation of a 3D Gaussian Beam Model

Calazan

Rodríguez

Jesus

2020

Computational Science and Its Applications – ICCSA 2020

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Despite the increasing performance of modern processors it is well known that the majority of models that account for 3D underwater acoustic predictions still require a high computational cost. In this context, this work presents strategies to enhance the computational performance of a ray-based 3D model. First, it is presented an optimized method for acoustic field calculations, that accounts for a large number of sensors. Second, the inherent parallelism of ray tracing and the high workload of 3D propagation are carefully considered, leading to the development of parallel algorithms for field predictions using a GPU architecture. The strategies were validated through performance analyses and comparisons with experimental data from a tank scale experiment, and the results show that model predictions are computationally efficient and accurate. The combination of numerical enhancements and parallel computing allowed to speedup model calculations for a large number of receivers.

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Beam tracing for two- and three-dimensional problems in ocean acoustics

Porter

2019

The Journal of the Acoustical Society of America

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Beam tracing is an extension of ray tracing that constructs beams around the central rays radiating from a source. Typically, a fan of such beams is used to represent a point source and the field at any given location is computed by coherently summing all contributing beams. On a slightly superficial level, one points to the following key benefits: (1) improved accuracy because the beams smooth out singularities of the ray-theoretic field, and (2) algorithmic advantages because eigenrays precisely connecting the source and the receiver do not need to be identified. One may argue about these considerations; however, beam tracing methods have emerged as a very important class of methods for computing ocean acoustic fields. Interestingly, the published literature has not kept up with the numerous advances in beam tracing, including algorithmic developments that are important to efficient and robust implementations. Furthermore, there are quite a few variants of beam tracing algorithms with very different characteristics. This article discusses these variants, significant advances in practical implementation, and performance characteristics.

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Three-dimensional model benchmarking for cross-slope wedge propagation

Cited by 6 publications

References 14 publications

Search Space Reduction for Localization and Tracking of an Acoustic Source

Search Space Reduction for Localization and Tracking of an Acoustic Source

Numerical Enhancements and Parallel GPU Implementation of a 3D Gaussian Beam Model

Beam tracing for two- and three-dimensional problems in ocean acoustics

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