摘要: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. Plain Language Abstract In preparation for the InSight mission that landed on Mars on November 26, 2018, we adapted an algorithm developed for Earth to measure the dependence of the speed of Rayleigh waves with frequency. These waves are useful to constrain the interior structure of planets because of their ability to resolve vertical changes in elastic parameters. This is because data at lower frequencies are sensitive to deeper structure than at higher frequency, a property called dispersion. The original method to measure this dispersion was modified for Mars because of the lack of a good starting interior reference model, and because of the larger uncertainties in estimating the quake parameters with one seismic station only. Here, we explain the method, which involves searching for hundreds of thousands of interior models that can explain the seismic recording and using them to determine the wavespeed as a function of frequency. We provide details about the modifications brought to the original algorithm, and test it on a blind data set provided to the Mars Structure Service team as well as on our own synthetic data set. We show that the method can find the real structure as long as a good starting model is available.