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Angular velocity estimation is critical for eddy current de-tumbling ofnoncooperative space targets. However, unknown model of the noncooperativetarget and few observation data make the model-based estimation methodschallenged. In this paper, a Data-driven Moving Horizon Estimation method isproposed to estimate the angular velocity of the noncooperative target withde-tumbling torque. In this method, model-free state estimation of the angularvelocity can be achieved using only one historical trajectory data thatsatisfies the rank condition. With local linear approximation, the Willemsfundamental lemma is extended to nonlinear autonomous systems, and the rankcondition for the historical trajectory data is deduced. Then, a data-drivenmoving horizon estimation algorithm based on the M step Lyapunov function isdesigned, and the time-discount robust stability of the algorithm is given. Inorder to illustrate the effectiveness of the proposed algorithm, experimentsand simulations are performed to estimate the angular velocity in eddy currentde-tumbling with only de-tumbling torque measurement.

Data-driven Moving Horizon Estimation for Angular Velocity of Space Noncooperative Target in Eddy Current De-tumbling Mission