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.

中文翻译：

---

使用压缩传感从环境噪声中提取多模态色散曲线

我们提出了一种用于从环境噪声中提取多模的压缩感知 (CS) 方法。我们使用两种方法解决 CS 逆问题：基于l ₁的优化算法和贝叶斯方法。进行了合成和现场数据示例以验证我们的方法。我们的方法提取的频散曲线与广泛使用的频率-贝塞尔变换（FJ）方法提取的色散曲线一致，但我们的方法比FJ方法更有效，可以提取更高分辨率的频谱图。我们的方法可以快速可靠地从环境噪声中提取多模态，从而促进环境噪声断层扫描的研究。