Aurora Flight Sciences (AFS), in collaboration with the MIT Space Systems Laboratory (MIT-SSL), proposed the Synthetic Imaging Maneuver Optimization (SIMO) program to develop a methodology, calibrated through hardware-in-the-loop testing, to optimize S/C maneuvers to more efficiently synthesize images for missions such as Stellar Imager (SI). Time and fuel-optimal maneuvers are only a part of the optimization problem. Selecting the maneuver waypoints (number and location) determines the quality of the synthesized image. The number of S/C, the size of the sub-apertures, and the type of propulsion system used also impacts imaging rate, propellant mass, and mission cost. Capturing all of these mission aspects in an integrated mission optimization framework helps mission designers to select the most appropriate architecture for meeting the needs and constraints of missions such as SI.