University of Illinois at Urbana-Champaign
Thursday, November 16 @ 3:30 p.m.
While basic orbit determination is a well understood problem, determining a full solution to the pose estimation and surface feature map of a target resident space object poses a greater challenge. Most orbit determination approaches suppose the use of active radar, frequently from the ground, but when the system making the determination is itself a spacecraft in a nearby orbit, traditional approaches are insufficient. This problem is further complicated when the chase spacecraft performing the determination is only equipped with a passive, monocular sensor such as a camera, rather than active radar or binocular vision. Initially a Rao-Blackwellized Particle Filter was implemented, however this classic approach was not able to converge within the desired timeframe and system observability. A new algorithm was developed which achieves the desired solution by using nonlinear programming applied to bundle adjustments over time, while absorbing core concepts from the simultaneous location and mapping field. An extended Kalman filter is used at long distance to determine the location of the target’s center-of-mass during approach phases while at long ranges. This algorithm is ultimately capable of on-board pose and orbit determination of its target, and has applications for automated spacecraft servicing, and proximity operations at near Earth asteroids.