Generalized Formulation of State and Parameter Estimation for Atmospheric Re-entry

Accurate navigation of Mars entry vehicles suggests that estimators should couple translational and rotational dynamics while accommodating time-varying atmospheric and aerodynamic uncertainty. This paper proposes a first step towards a generalized framework with nonlinear state and parameter (i.e., aerodynamic and atmospheric) estimation that is applicable to most entry vehicle design configurations. The framework described in this paper fuses inertial-measurement unit (IMU) measurements with distributed surface-pressure data to estimate coupled translational and rotational dynamics. Atmospheric density and pressure are included as parameters in augmented state vector, enabling the filter to decouple aerodynamic from environmental uncertainty. Presented results demonstrate that it is promising to identify aerodynamic coefficients in real-time via direct calculation based on the estimated states and IMU measurements. The resulting framework could support further research on aerodynamic parameter identification, observability studies, and closed-loop adaptive estimation.