Estimation of Uncooperative Satellite Inertia Parameters for Space Debris Removal Using Particle Swarm Optimization

Although passive mitigation measures have been put into place to ensure the long-term sustainability of space activ-ities, numerous studies have shown that in order to stabilize the growth of the orbital debris population, active removal of the largest debris in Earth orbit, such as abandoned spacecraft and rocket bodies, is still necessary. In active debris removal scenarios, the target is generally uncooperative and therefore non-communicative (e.g., through some easily recognizable arti-ficial markers or transponder) with the servicing spacecraft and cannot exchange information and safely perform the docking or berthing operations. Additionally, essential information on the form and inertia characteristics of the space target may have altered due to the prolonged period in orbit (e.g., due to exhaustion of fuel, collisions, or explosions). Additionally, unknown objects such as large debris pieces will have unknown inertia properties. This paper proposes a method of inertia esti-mation of a rotating target assuming a torque-free environment. Estimation is performed through the use of Particle Swarm Optimization (PSO) utilizing attitude observations of the target (quaternion data). The solution space for PSO particles is an R6 vector that can be mapped to inertia tensor matrix space, which represents an estimate of the target's (symmetric) inertia tensor. Attitude motion is propagated using Euler's equations to generate estimated measurements which are then compared to experimental attitude measurements for validation