Reconstruct the ambient noise source from the multi-frequency sparse correlation data
For researchers in inverse problems and acoustic imaging, this method offers a computationally efficient approach to source reconstruction with sparse data, though it is an incremental improvement over existing factorization techniques.
The paper develops a multi-frequency factorization method to reconstruct the spatial support of ambient noise sources using sparse correlation data, demonstrating effectiveness in 2D and 3D numerical experiments.
In this paper, we develop a novel multi-frequency factorization method to reconstruct the spatial support of the ambient noise source. The proposed method only requires sparse correlation data and has low computational cost. Numerical experiments in two and three dimensions are presented to demonstrate the effectiveness of the proposed method.