• Electronics Optics & Control
  • Vol. 25, Issue 5, 41 (2018)
ZONG Shiguang, LIU Tao, and LIANG Shanyong
Author Affiliations
  • [in Chinese]
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    DOI: 10. 3969/j. issn. 1671-637x. 2018. 05. 009 Cite this Article
    ZONG Shiguang, LIU Tao, LIANG Shanyong. Interference Resource Allocation Based on Improved Genetic Algorithm[J]. Electronics Optics & Control, 2018, 25(5): 41 Copy Citation Text show less

    Abstract

    To improve the efficiency of networked radar interference, an improved genetic algorithm was designed and applied to interference resource allocation. As to the three allocation models (one-by-one, more-by-less, and less-by-more), the allocation plans were made and the interference benefit value was calculated respectively. Compared with the results of other algorithms, the improved genetic algorithm not only gets better allocation results and benefit value, but also needs fewer iterative times, which verify the high efficiency of this algorithm.
    ZONG Shiguang, LIU Tao, LIANG Shanyong. Interference Resource Allocation Based on Improved Genetic Algorithm[J]. Electronics Optics & Control, 2018, 25(5): 41
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