Orbit Selection based on an Integration Macro-Micro Collision Risk Assessment Algorithm

Space debris has become a global concern as human space activities intensify; Space Surveillance Networks have cataloged over 36,000 objects, posing persistent hazards to on-orbit spacecraft. This paper proposes an integrated macro-micro collision-risk framework for orbit selection that unifies density-based risk mapping with event-level conjunction analysis. The operational space is voxelized in right ascension, declination, and altitude to estimate spatial density; a Kessler-type formulation converts density and relative-velocity statistics into a macroscopic collision probability, yielding a low-risk initial orbit. Objects intersecting the operational corridor are then screened, and precise relative motion is propagated to detect close approaches under a distance threshold; associated avoidance maneuvers and fuel consumption are accounted for. The overall design is cast as a multi-objective optimization that minimizes cumulative collision probability and AV subject to orbital-dynamics, mission, and safety constraints. By jointly considering macroscopic collision likelihood and microscopic events, the method provides a principled basis for selecting safer, fuel-efficient orbits.