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Article Dans Une Revue International Journal of Computational Intelligence Systems Année : 2016

Optimization of small satellite constellation design for continuous mutual regional coverage with multi-objective genetic algorithm,

Résumé

This paper describes the application of an evolutionary optimization method to design satellite constellation for continuous regional coverage without intersatellite links. This configuration, called mutual coverage, is related to some technical limitations that exist on small satellite technology. The coverage of the north Algerian seismological network is taken as an example of application. A Multi Objective Genetic Algorithm (MOGA) is used to make a trade-off between the improvement of the coverage rate, the minimization of the total number of satellites and the reduction of the satellites' altitude. First, some experiments have been performed to find the weight distribution of the fitness function that shows the most significant improvement of the average fitness function. Then, some optimized constellation designs are given for different ranges of altitude and it is shown that the size of the MOGA constellation design is significantly reduced compared to the traditional geometrical design.

Dates et versions

hal-01347277 , version 1 (20-07-2016)

Identifiants

Citer

I. Meziane-Tani, G. Metris, G. Lion, Anne Deschamps, F.T. Bendimerad, et al.. Optimization of small satellite constellation design for continuous mutual regional coverage with multi-objective genetic algorithm,. International Journal of Computational Intelligence Systems, 2016, 9 (4), pp.627-637. ⟨10.1080/18756891.2016.1204112⟩. ⟨hal-01347277⟩
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