An ensemble Kalman filter approach based on level set parameterization for acoustic source identification using multiple frequency information
arXiv:1907.12187
summary
The paper proposes a statistical inversion method that combines an ensemble Kalman filter with level set parameterization to reconstruct spatially varying acoustic sources from noisy multi‑frequency measurements on a remote surface.
Abstract
The spatial dependent unknown acoustic source is reconstructed according noisy multiple frequency data on a remote closed surface. Assume that the unknown function is supported on a bounded domain. To determine the support, we present a statistical inversion algorithm, which combines the ensemble Kalman filter approach with level set technique. Several numerical examples show that the proposed method give good numerical reconstruction.
Topics & keywords
#acoustic source identification#ensemble kalman filter#level set method#inverse problems#multiple frequency dataensemble Kalman filterlevel set parameterizationacoustic source reconstructionstatistical inversionnumerical examples