# An ensemble Kalman filter approach based on level set parameterization for acoustic source identification using multiple frequency information

## TL;DR

This paper introduces a novel ensemble Kalman filter method combined with level set techniques for reconstructing unknown acoustic sources from noisy multi-frequency data, demonstrating effective numerical results.

## Contribution

The paper presents a new statistical inversion algorithm integrating ensemble Kalman filter with level set methods for acoustic source support determination.

## Key findings

- Effective reconstruction of acoustic sources from noisy data
- Successful numerical examples demonstrating method accuracy
- Supports multi-frequency data integration

## 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.