Hyper{X Post{Flight Trajectory Reconstruction

The formulation and development of a trajectory reconstruction tool for the NASA X-43A/Hyper-X high-speed research vehicle and its implementation for the reconstruction and analysis of flight-test data are discussed. Extended Kalman filtering techniques are employed to reconstruct the trajectory of the vehicle, based on numerical integration of inertial measurement data along with redundant measurements of the vehicle state provided by global positioning system measurements of position and velocity. The equations of motion are formulated to include the effects of several systematic error sources, the values of which may also be estimated by the filtering routines. Additionally, smoothing algorithms have been implemented in which the final value of the state (or an augmented state that includes other systematic error parameters to be estimated) and covariance are propagated back to the initial time to generate the best-estimated trajectory, based on all available data. The methods are applied to the problem of reconstructing the trajectory of the Hyper-X vehicle from flight data.

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