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- Title
Extraction of Multimodal Dispersion Curves From Ambient Noise With Compressed Sensing.
- Authors
Gao, Lina; Zhang, Wenqiang; Zhang, Zhenguo; Chen, Xiaofei
- Abstract
We propose a compressed sensing (CS) method for extracting multimodes from ambient noise. We solve the CS inverse problem by using two methods: an l1‐based optimization algorithm and a Bayesian method. Synthetic and field data examples are conducted to validate our method. The dispersion curves extracted by our method are consistent with those extracted by the widely used frequency‐Bessel transform (F‐J) method, but our method is more efficient and can extract higher‐resolution spectrograms than the F‐J method. Our method can quickly and reliably extract multimodes from ambient noise, thereby facilitating studies of ambient noise tomography. Key Points: We present a novel method to extract multimodal dispersion curves from ambient noise with compressed sensingWe validate our method by implementing both synthetic tests and field examplesOur method of extracting multimodes is very efficient and has a high resolution
- Subjects
COMPRESSED sensing; SIGNAL sampling; DISPERSION (Chemistry); AMBIENT sounds; BESSEL functions
- Publication
Journal of Geophysical Research. Solid Earth, 2021, Vol 126, Issue 6, p1
- ISSN
2169-9313
- Publication type
Article
- DOI
10.1029/2020JB021472