2012 A.1.2 Identification and Evaluation of iCubeSat Mission Architectures


Mathew Zwack (1), Stephen Edwards (1), Jonathan Sharma (1), Chris May (1), and Dimitri Mavris (1)

  1. Georgia Institute of Technology


A.1 – Technology – System Issues for Interplanetary CubeSat Missions


Systems Engineering, Multi-Attribute Decision Making, architecture evaluation


Since the genesis of the CubeSat standard, the usage of CubeSats has become increasingly popular in commercial, military, and academic applications alike. CubeSats typically serve as cost effective test-beds and demonstrators for various in-space technologies in earth orbit. However, their low cost paradigm is beginning to extend into many other areas of satellite operations. With the advent of new technologies, the use of CubeSats for missions extending far beyond earth orbit can be realized. The first step towards the realization of interplanetary CubeSat (iCubeSat) missions is the identification and evaluation of candidate mission architectures. The idea of an iCubeSat is relatively new and it is, therefore, important to evaluate as many mission architectures as possible while avoiding the use of historical experience as a down-selection tool. This study uses various pre-conceptual level systems engineering techniques to identify and evaluate candidate architectures for a general iCubeSat mission. The architectures are assembled using a Morphological Matrix of Alternatives (MoA), and are then evaluated against a list of attributes using an Analytical Hierarchy Process (AHP). Application of AHP allows for the use of qualitative data in performing a quantitative assessment, enabling a rapid evaluation of all the possible mission architectures that can be defined by the MoA. From this analysis, the Pareto optimal solutions are identified, providing insight into the driving trades that exist for the novel concept of iCubeSat missions. A method for identifying candidates from the Pareto optimal solutions for further study is presented using Multi-Attribute Decision Making (MADM) techniques to rank the architectures based upon a prioritization of mission objectives.



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