InSight’s seismometer package SEIS was placed on the surface of Mars at about 1.2 m distance from the thermal properties instrument HP3 that includes a self-hammering probe. Recording the hammering noise with SEIS provided a unique opportunity to estimate the seismic wave velocities of the shallow regolith at the landing site. However, the value of studying the seismic signals of the hammering was only realised after critical hardware decisions were already taken. Furthermore, the design and nominal operation of both SEIS and HP3 are non-ideal for such high-resolution seismic measurements. Therefore, a series of adaptations had to be implemented to operate the self-hammering probe as a controlled seismic source and SEIS as a high-frequency seismic receiver including the design of a high-precision timing and an innovative high-frequency sampling workflow. By interpreting the first-arriving seismic waves as a P-wave and identifying first-arriving S-waves by polarisation analysis, we determined effective P- and S-wave velocities of vP = 119+45-21 m/s and vS = 63+11-7 m/s, respectively, from around 2,000 hammer stroke recordings. These velocities likely represent bulk estimates for the uppermost several 10’s of cm of regolith. An analysis of the P-wave incidence angles provided an independent vP/vS ratio estimate of 1.84+0.89-0.35 that compares well with the traveltime based estimate of 1.86+0.42-0.25. The low seismic velocities are consistent with those observed for low-density unconsolidated sands and are in agreement with estimates obtained by other methods.

One of the goals of the InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) 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 (VS) models from a single seismogram. This method was adapted to Mars from a technique recently developed for Earth (Xu & Beghein, 2019). Monte Carlo Markov Chains (MCMC) seek an ensemble of one dimensional (1-D) VS 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 paper, 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 MSS blind test data and our own synthetic data, which included realistic noise levels based on the noise recorded by InSight.

In early 2019, NASA’s InSight lander successfully deployed a single three-component very broadband seismometer (VBB) on the surface of Mars to detect and characterize marsquakes. Using these data, we present a method to infer the source mechanisms of marsquakes from waveforms of P and S waves recorded at a single station. We show that the three events with the highest signal-to-noise ratio (SNR) and a robust distance estimate S0173a, (May 23rd 2019), S0235b, (July 27th 2019) and S0183a, (June 3rd 2019) are all likely the results of normal faulting, suggesting an extensional regime mainly oriented south-east north-west in the respective source regions, Cerberus Fossae and Orcus Patera. We quantify the uncertainty of our solutions by comparing results of a direct inversion with a grid-search method.

The NASA InSight lander successfully placed a seismometer on the surface of Mars. Alongside, a hammering device was deployed that penetrated into the ground to attempt the first measurements of the planetary heat flow of Mars. The hammering of the heat probe generated repeated seismic signals that were registered by the seismometer and can potentially be used to image the shallow subsurface just below the lander. However, the broad frequency content of the seismic signals generated by the hammering extends beyond the Nyquist frequency governed by the seismometer's sampling rate of 100 samples per second. Here, we propose an algorithm to reconstruct the seismic signals beyond the classical sampling limits. We exploit the structure in the data due to thousands of repeated, only gradually varying hammering signals as the heat probe slowly penetrates into the ground. In addition, we make use of the fact that repeated hammering signals are sub-sampled differently due to the unsynchronised timing between the hammer strikes and the seismometer recordings. This allows us to reconstruct signals beyond the classical Nyquist frequency limit by enforcing a sparsity constraint on the signal in a modified Radon transform domain. Using both synthetic data and actual data recorded on Mars, we show how the proposed algorithm can be used to reconstruct the high-frequency hammering signal at very high resolution. In this way, we were able to constrain the seismic velocity of the top first meter of the Martian regolith.