Streamlining the Design Tradespace for Earth Imaging Constellations

Distributed Spacecraft Missions (DSMs) are gaining momentum in their application to Earth Observation (EO) missions owing to their unique ability to increase observation sampling in spatial, spectral, angular and temporal dimensions simultaneously. DSM design includes a much larger number of variables than its monolithic counterpart, therefore, Model-Based Systems Engineering (MBSE) has been often used for preliminary mission concept designs, to understand the trade-offs and interdependencies among the variables. MBSE models are complex because the various objectives a DSM is expected to achieve are almost always conflicting, non-linear and rarely analytical. NASA Goddard Space Flight Center is developing a pre-Phase A tool called "Trade-space Analysis Tool for Constellations" (TAT-C) to initiate constellation mission design. The tool will allow users to explore the tradespace between various performance, cost and risk metrics (as a function of their science mission) and select Pareto optimal architectures that meet their requirements. This paper focuses on the tradespace search and how it can be streamlined by combining physical rules, as well as well-designed orbit and coverage computations, thus yielding significant speed-ups. Two use cases are shown as representative examples of the utility of TAT-C generated trades, and results are preliminarily validated against AGI's Systems Tool Kit.