On August 5th 2012, The Mars Science Laboratory entry vehicle successfully entered Mars'atmosphere and landed the Curiosity rover on its surface. A Kalman filter approach hasbeen implemented to reconstruct the entry, descent, and landing trajectory based on all availabledata. The data sources considered in the Kalman filtering approach include the inertialmeasurement unit accelerations and angular rates, the terrain descent sensor, the measuredlanding site, orbit determination solutions for the initial conditions, and a new set of instrumentationfor planetary entry reconstruction consisting of forebody pressure sensors, knownas the Mars Entry Atmospheric Data System. These pressure measurements are unique forplanetary entry, descent, and landing reconstruction as they enable a reconstruction of thefreestream atmospheric conditions without any prior assumptions being made on the vehicleaerodynamics. Moreover, the processing of these pressure measurements in the Kalman filterapproach enables the identification of atmospheric winds, which has not been accomplishedin past planetary entry reconstructions. This separation of atmosphere and aerodynamicsallows for aerodynamic model reconciliation and uncertainty quantification, which directlyimpacts future missions. This paper describes the mathematical formulation of the Kalmanfiltering approach, a summary of data sources and preprocessing activities, and results of thereconstruction.
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