Disaggregated constellation optimization applied to environmental monitoring
- Paper number
IAC-19,B6,2,1,x49419
- Author
Mrs. Katherine Wagner, United States, Virginia Polytechnic Institute and State University
- Coauthor
Dr. Kevin Schroeder, United States, Virginia Tech
- Coauthor
Dr. Jonathan Black, United States, Virginia Tech
- Year
2019
- Abstract
Disaggregation of space-based capabilities can offer significant advantages in cost and resiliency over traditional, monolithic spacecraft. Hosted payload disaggregation, in which secondary payloads are placed on spacecraft performing a separate mission, offers particular challenges as a problem where the mission designer may have no control over the ultimate behavior of the satellites. We present a novel methodology for designing constellations using hosted payload disaggregation, considering the impact on mission success when the host satellite behavior is off-nominal, such as in the event of system failure or of changing primary payload orbit requirements. A multiobjective genetic algorithm is used to assign the host payload to the hosting satellites. Linear programming techniques are leveraged to determine mission performance in the event of system failure as part of the genetic algorithm fitness evaluation step. Heuristic methods are used in post-processing to determine the impact of orbit changes on the optimal solution performance. As a test case, the methodology is applied to the task of designing an environmental monitoring constellation using only hosted payloads. The satellites on which the payloads are hosted are selected from planned commercial sector satellite missions, including the OneWeb and SpaceX megaconstellations. The constellation’s performance is compared to that of the Sentinel satellites with respect to the requirements outlined in the Copernicus program.
- Abstract document
- Manuscript document
IAC-19,B6,2,1,x49419.pdf (🔒 authorized access only).
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