Estimation and Prediction of Orbital Debris Reentry Trajectories

Tracking and prediction of orbital debris trajectories have recently received a great deal of attention due to the increasing proliferation of such objects and the hazard they pose to operational spacecraft. Most analyseshave focused on in-orbit dynamics, such as the probability of collision with low-orbiting satellites, especially the International Space Station. Less attention has been given to the problem of reentry estimation and impact prediction. During reentry, aerodynamic forces dominate the dynamics, which presents a challenge to the trajectory estimation problem because the relevant characteristics of debris (size, shape, and mass) needed to model the trajectory accurately are largely unknown. A ground-based trajectory estimation method is described that attempts to determine simultaneously the unknown time-varying ballistic coefficients with the state vector using an extended Kalman filter. This filter estimates the unknown ballistic coefficients by using dynamic process noise parameters based on an integral state model. A posteriori information from the filter is processed by a Monte Carlo algorithm to predict the impact location. Simulation results are presented and suggest a high degree of accuracy in both the estimation and prediction stages.