Relative motion and thrust estimation of a non-cooperative maneuvering target with adaptive filter

With the rapid increase in the number of spacecraft in outer space, the unknown maneuvers of a spacecraft significantly increase the probability of a collision between neighborhoods. In order to guarantee the safety of an operational spacecraft, we need to estimate and predict the relative trajectories of a non-cooperative target in real time. Traditional filter routines are ineffective when the target spacecraft performs unknown continuous maneuvers. In this work, we focus on the development of relative estimators with enhanced robustness against unknown maneuvers. First, a variable state dimension estimator based on filter switching and covariance inflation is proposed to adaptively cope with a constant unknown maneuver. To strengthen the robustness in response to the time-varying maneuvers, a novel observer-enhanced Kalman filter is subsequently proposed by incorporating an observer into the filtering routines. Finally, the performance of the proposed estimators is evaluated with a series of numerical simulations, both the advantages and the disadvantages are analyzed using the simulation results.