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Gaussian Beam Migration for Wide-Area Deep Ocean Floor Mapping

Charous, A., W.H. Ali, P. Ryu, D. Brown, K. Arsenault, B. Cho, K. Rimpau, A. March, and P.F.J. Lermusiaux, 2023. Gaussian Beam Migration for Wide-Area Deep Ocean Floor Mapping. In: OCEANS '23 IEEE/MTS Gulf Coast, 25–28 September 2023. doi:10.23919/OCEANS52994.2023.10337362

Cost-effective seafloor mapping at high resolution is yet to be attained. A possible solution consists of using a mobile, wide-aperture, sparse array with subarrays distributed across multiple autonomous surface vessels. Such wide-area mapping with multiple dynamic sources and receivers require accurate modeling and processing systems for imaging the seabed. In this paper, we focus on computational schemes and challenges for such high-resolution acoustic imaging or migration. Starting from the imaging condition from the adjoint-state method, we derive a closed-form expression for Gaussian beam migration in stratified media. We employ this technique on simulated data and on real data collected with our novel acoustic array over shipwrecks in the Boston Harbor. We compare Gaussian beam migration with diffraction stack and Kirchhoff migration, and we find that Gaussian beam migration produces the clearest images with the fewest artifacts.