Design and Optimization of a Disaggregated Constellation for Space Situational Awareness

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SSC-2015-VIII-3.pdf (385.48 KB)
Author(s)
Snow, Adam
Den Boer, Angela
Alexander, Luke
Holzinger, Marcus J.
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Daniel Guggenheim School of Aerospace Engineering
The Daniel Guggenheim School of Aeronautics was established in 1931, with a name change in 1962 to the School of Aerospace Engineering
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https://hdl.handle.net/1853/74035
Abstract
The number of objects in earth orbit is increasing at an unprecedented rate comma increasing the need for space situational awareness. A novel approach for the design and optimization of a disaggregated and scalable satellite constellation for space object detection is proposed. Discussions of the payload, design objectives and detection constraints are presented with respect to the design process period to understand the effects of detection capabilities for a space based sensor, A series of simulations were performed using the publicly available JSpOC catalog through varying constellation architectures. A genetic algorithm was employed to explore the objective space of constellation architectures in order to optimize mission performance. In particular, this optimization effort seeks to maximize economic return of the space mission by quantifying the financial value of mission performance.
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Date
2015-08
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Text
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Paper
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