Uncertainty Quantification for Mars Entry, Descent, and Landing Reconstruction Using Adaptive Filtering

Mars entry, descent, and landing trajectories are highly dependent on the vehicle's aerodynamics and the planet's atmospheric properties during the day of flight. A majority of previous Mars entry trajectory and atmosphere reconstruction analyses do not simultaneously estimate the flight trajectory and the uncertainties in the atmospheric and aerodynamics models. Adaptive filtering techniques, when combined with traditional trajectory estimation methods, can improve the knowledge of the aerodynamic coefficients and atmospheric properties, while also estimating the confidence interval for these parameters. Simulated data sets with known truth data are used in this study to show the improvement in state and uncertainty estimation by using adaptive filtering techniques. Such a methodology can then be implemented on existing and future Mars entry data sets to determine the aerodynamic and atmospheric uncertainties and improve engineering design tools.