One of the goals of the Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) mission is to constrain the interior structure of Mars. We present a hierarchical transdimensional Bayesian approach to extract phase velocity dispersion and interior shear‐wave velocity (V_S) models from a single seismogram. This method was adapted to Mars from a technique recently developed for Earth (Xu & Beghein, 2019, https://doi.org/10.1093/gji/ggz133). Monte Carlo Markov Chains seek an ensemble of one dimensional (1‐D) V_S models between a source and a receiver that can explain the observed waveform. The models obtained are used to calculate the phase velocities of fundamental and higher modes at selected periods, and a subsequent analysis is performed to assess which modes were reliably measured. An advantage of our approach is that it can also fit unknown data noise, which reduces the risk of overfitting the data. In addition, uncertainties in the source parameters can be propagated, yielding more accurate model parameter uncertainties. In this study, we first present our technique and discuss the challenges stemming from using a single station to characterize both structure and the source and from the absence of a Mars reference model. We then demonstrate the method feasibility using the Mars Structure Service blind test data and our own synthetic data, which included realistic noise levels based on the noise recorded by InSight.

中文翻译：

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利用地震波形测量火星上的基本和高模表面波频散

使用地震勘探，大地测量与热传输（InSight）任务进行的内部勘探的目标之一是限制火星的内部结构。我们提出了一个分层跨次贝叶斯方法提取相速度频散和内部剪切波速（V_小号）模型从一个单一的地震记录。从最近为地球开发的技术（Xu＆Beghein，2019，https://doi.org/10.1093/gji/ggz133）改编成火星方法。蒙特卡洛·马可夫链（Monte Carlo Markov Chains）寻找一维（1-D）V _S的集合源和接收器之间的模型可以解释观察到的波形。获得的模型用于计算选定周期内基本模态和更高模态的相速度，并进行后续分析以评估可靠测量了哪些模态。我们方法的优点是它还可以适应未知数据噪声，从而降低了过拟合数据的风险。另外，可以传播源参数中的不确定性，从而产生更准确的模型参数不确定性。在这项研究中，我们首先介绍我们的技术，并讨论由于使用单个测站表征结构和震源的特征以及缺少火星参考模型而带来的挑战。然后，我们使用Mars Structure Service盲测数据和我们自己的综合数据证明该方法的可行性，