Date of Award


Document Type


Degree Name

Master of Science in Systems Engineering


Department of Systems Engineering and Management

First Advisor

Richard G. Cobb, PhD


Space is a contested, congested, and competitive environment where space situational awareness (SSA) is a key factor in the long term sustainability of space as a national interest. Space-based SSA conducted by inspector satellites is critical to the detecting, tracking, and attribution of actions in space. Thus, space-based fuel-optimal maneuvers are essential to increasing mission life and improving the capability of inspector satellites working to characterize resident space objects (RSOs) in geosynchronous orbit (GEO). Additionally, on-orbit inspection missions can be characterized by multiple waypoint visits where an inspector is accomplishing a set of proximity operation mission objectives through the visit of multiple waypoints signifying viewing angles, natural motion circumnavigation (NMC) injection states, and rendezvous locations. Traditionally, the combinatorial and trajectory optimization aspects of these space-based multiple waypoint visits have been solved in a segregated manner. This thesis presents a Mixed Integer Programming (MIP) framework, in which the combinatorial and trajectory optimization nature of these problems are coupled resulting in the fuel-optimal guidance for complex rendezvous and proximity operation missions. First, a Mixed Integer Linear Programming (MILP) formulation is used to solve for the fuel optimal guidance of an inspector visiting multiple viewing angles, defined by waypoints, around a single RSO. This mission is subject to keep-out-zones (KOZ) and mission time constraints. Additionally, the initial MILP problem is extended to a linear cooperative control formulation where two inspectors are working together to accomplish the mission objectives. Both MILP problems are solved to global optimality using a commercial MIP solver.

AFIT Designator


DTIC Accession Number