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An Evolved Antenna for Deployment on Nasa’s Space Technology 5 Mission

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Book cover Genetic Programming Theory and Practice II

Part of the book series: Genetic Programming ((GPEM,volume 8))

Abstract

We present an evolved X-band antenna design and flight prototype currently on schedule to be deployed on NASA’s Space Technology 5 (ST5) spacecraft. Current methods of designing and optimizing antennas by hand are time and labor intensive, limit complexity, and require significant expertise and experience. Evolutionary design techniques can overcome these limitations by searching the design space and automatically finding effective solutions that would ordinarily not be found. The ST5 antenna was evolved to meet a challenging set of mission requirements, most notably the combination of wide beamwidth for a circularly-polarized wave and wide bandwidth. Two evolutionary algorithms were used: one used a genetic algorithm style representation that did not allow branching in the antenna arms; the second used a genetic programming style tree-structured representation that allowed branching in the antenna arms. The highest performance antennas from both algorithms were fabricated and tested, and both yielded very similar performance. Both antennas were comparable in performance to a hand-designed antenna produced by the antenna contractor for the mission, and so we consider them examples of human-competitive performance by evolutionary algorithms. As of this writing, one of our evolved antenna prototypes is undergoing flight qualification testing. If successful, the resulting antenna would represent the first evolved hardware in space, and the first deployed evolved antenna.

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© 2005 Springer Science+Business Media, Inc.

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Lohn, J.D., Hornby, G.S., Linden, D.S. (2005). An Evolved Antenna for Deployment on Nasa’s Space Technology 5 Mission. In: O’Reilly, UM., Yu, T., Riolo, R., Worzel, B. (eds) Genetic Programming Theory and Practice II. Genetic Programming, vol 8. Springer, Boston, MA. https://doi.org/10.1007/0-387-23254-0_18

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  • DOI: https://doi.org/10.1007/0-387-23254-0_18

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-387-23253-9

  • Online ISBN: 978-0-387-23254-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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