Hybrid Flush/Synthetic Air Data Filter for Entry Vehicle Atmospheric State Estimation

A hybrid flush/synthetic air data sensing filter using Kalman–Schmidt and Rauch–Tung–Striebel smoothers was developed to obtain entry vehicle atmosphere estimates. The filter/smoother blends information from pressure sensors distributed on the heat shield with measurements of the vehicle aerodynamic forces and moments computed from mass properties, inertial measurement unit data, and previous estimates of the atmosphere. The filter produces estimates of atmospheric conditions along the entry trajectory and systematic error estimates to reconcile the differences between the pressure and aerodynamic data sources. The filter was applied to data acquired during the Mars Science Laboratory and Mars 2020 entry, descent, and landing at the Gale and Jezero craters, respectively. The results show that the hybrid filter produces estimates of freestream flight condition with lower uncertainty than either the flush or synthetic air data algorithms. The filter accomplished this result by incorporating additional data and computing estimates of systematic error parameters in the pressure data and aerodynamic model to further reduce the uncertainties.