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Geometric Stochastic Ray Tracing
In this (unfunded side) project we developed a new model for acoustic ray tracing that admits stochastic diffusion as a function of uncertainty in the sound speed profile. The approach uses recent tools for analysis of differential motion on the special Euclidean group. One target application that would benefit from this approach is ranged-based localization of underwater vehicles because the uncertainty of the ray positions is more accurately represented as a function of the uncertainty of the sound speed profile.
Figure 1.1: Model overview and relation to existing work.
To illustrate the capabilities of this new model, we compute the stochastic ray traces with an uncertain sound speed profile computed from data observed in the Beaufort Sea.
Figure 1.3: Left to right: Uncertain SSP, Nominal ray traces (blue) with realizations of stochastic rays (gray), Distribution of errors in SSP, Distribution of ray trajectories at approximately 40km for a ray (a) in the Beaufort lens and (b) reflected about the surface.
Status: | Ongoing since December 2023 |
People: | Tyler Paine, Eeshan Bhatt |
Recent Publications
2024 (1 item)
- Tyler Paine, Tyler, EeShan Bhatt, Geometric Stochastic Ray Propagation Using the Special Euclidean Group, JASA Express Letters, (4)4, 046002, April, 2024. (bibtex)
Document Maintained by: tpaine@mit.edu
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