The problem of constellation design presents many difficulties in the form of multiple, competing objectives and a complex design space. Past approaches to solving this problem have been to limit the number of objectives and/or simplify the geometry (such as restricting the design procedure to using only circular orbits) so that a tractable solution is obtainable. The genetic algorithm (GA) has been used in many design problems, but has seen limited application to the problem of constellation design. The GA has the ability to handle objectives of mixed (continuous and discrete) type and complex design spaces that do not have convenient analytical representations. With these capabilities, it becomes possible to consider the use of eccentric, inclined orbits for designing constellations efficiently. A method to evaluate coverage associated with ellipitical orbits via a streets-of-coverage approach was derived for this effort. This paper describes a method for applying a GA in a gaming approach for multiobjective design of satellite constellations for zonal coverage. The algorithm is applied to a northern hemisphere coverage problem, a CONUS-like coverage problem, and an ELLIPSO™-like coverage problem. Results are presented that suggest elliptic orbits may be beneficial to reduce the number of satellites needed for certain coverage problems.


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    Title :

    Satellite Constellation Design for Zonal Coverage Using Genetic Algorithms


    Additional title:

    J of Astronaut Sci


    Contributors:

    Published in:

    Publication date :

    1999-09-01


    Size :

    22 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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