Autonomous generation of observation schedules for tracking satellites with structured-chromosome GA optimisation
Greco, Cristian and Gentile, Lorenzo and Filippi, Gianluca and Minisci, Edmondo and Vasile, Massimiliano and Bartz-Beielstein, Thomas; (2019) Autonomous generation of observation schedules for tracking satellites with structured-chromosome GA optimisation. In: 2019 IEEE Congress on Evolutionary Computation. IEEE, NZL, pp. 497-505. ISBN 9781728121536 (https://doi.org/10.1109/CEC.2019.8790101)
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Abstract
This paper addresses the problem of autonomous scheduling of space objects' observations from a network of tracking stations to enhance the knowledge of their orbit while respecting allocated resources. This task requires the coupling of a state estimation routine and an optimisation algorithm. As for the former, a sequential filtering approach to estimate the satellite state distribution conditional on received indirect measurements has been employed. To generate candidates, i.e. observation campaigns, a Structured-Chromosome Genetic Algorithm optimiser has been developed, which is able to address the issue of handling mixed-discrete global optimisation problems with variable-size design space. The search algorithm bases its strategy on revised genetic operators that have been reformulated for handling hierarchical search spaces. The presented approach aims at supporting the space sector by tracking both operational satellites and non-collaborative space debris in response to the challenge of a constantly increasing population size in the near Earth environment. The potential of the presented methodology is shown by solving the optimisation of a tracking window schedule for a very low Earth satellite operating in a highly perturbed dynamical environment.
ORCID iDs
Greco, Cristian ORCID: https://orcid.org/0000-0001-5996-2114, Gentile, Lorenzo, Filippi, Gianluca, Minisci, Edmondo ORCID: https://orcid.org/0000-0001-9951-8528, Vasile, Massimiliano ORCID: https://orcid.org/0000-0001-8302-6465 and Bartz-Beielstein, Thomas;-
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Item type: Book Section ID code: 68574 Dates: DateEvent10 June 2019Published7 March 2019AcceptedNotes: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Subjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Mechanical and Aerospace Engineering
Strategic Research Themes > Ocean, Air and SpaceDepositing user: Pure Administrator Date deposited: 25 Jun 2019 11:00 Last modified: 29 Oct 2024 01:27 URI: https://strathprints.strath.ac.uk/id/eprint/68574