A QP-based iterative approach to on-line inertia estimation for non-cooperative tumbling spacecraft
J. Rebollo, Francisco Gavilan, Rafael Vázquez, Daniel Limón · 2024
An iterative algorithm based on the solution of a Quadratic Programming (QP) problem is presented for online inertia estimation of tumbling uncontrolled spacecraft using discrete attitude measurements. This estimation is crucial for various applications, chiefly among them active debris removal, where the rotational state of tumbling debris must be accurately determined to enable safe approach and capture maneuvers. Linear constraints are employed to guarantee that the optimization problem solution is consistent with the physical constraints of the inertia tensor. The inertia estimation, derived from discrete mechanics principles, can be formally posed as a Semidefinite Programming (SDP) optimization problem. To reduce the complexity, a local parametrization compatible with the structure of inertia tensors is proposed to derive a QP algorithm. Numerical simulations are used to validate the effectiveness of this methodology and demonstrate its potential for real-time implementation in scenarios involving uncontrolled tumbling spacecraft. The proposed QP-based iterative approach offers a computationally efficient alternative to SDP methods while maintaining estimation accuracy, making it well-suited for on-board implementation with limited computational resources.