Intelligent collaborative sensing for detection and removal of small distributed space debris

Abstract

Space debris in the 1-10 cm diameter regime presents a particular hazard to future operations in low Earth orbit (LEO). These objects are too small to be reliably detected by terrestrial radar or telescopes, but too large for their impacts to be mitigated with Whipple shielding. This paper addresses this hazard by presenting a methodology for space-based detection and active debris removal (ADR) via novel intelligent collaborative sensing and efficient decentralized data fusion. In simulation, we demonstrate that a small heterogeneous constellation of co-orbiting satellites using attentional neural networks can autonomously share information and maneuver in a cooperative game to de-orbit space debris (e.g. with a mechanical arm or pulsed laser) while minimizing total energy consumption and collision risk in the constellation. Particular focus is given to the robustness and effectiveness of the developed collaborative sensing system with respect to sensor uncertainties and transient changes in observability between nodes.