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A soft resource optimization method for improving the resilience of UAV swarms under continuous attack

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  • Li, Hongxu
  • Sun, Qin
  • Zhong, Yuanfu
  • Huang, Zhiwen
  • Zhang, Yingchao

Abstract

Resilience is a comprehensive metric that measures the ability of an unmanned aerial vehicle (UAV) swarm to resist and recover after being attacked. Improving resilience is critical when UAV swarms still need to perform their intended mission after being attacked. Although studies have shown that adding UAVs or changing communication links can improve the resilience of UAV swarms, these enhancement methods cannot be the first choice due to the limitations of physical resources and mission benefits. In addition, these studies focus more on the single attack but ignore the continuous attack. Therefore, a method for improving the resilience of UAV swarms under continuous attack is proposed in this paper from the perspective of soft resource optimization. Firstly, a resilience measurement method considering cost and benefit is proposed. Unlike previous studies, the resilience measurement method given in this paper is from the perspective of missions rather than the structure of swarms. Secondly, a soft resource optimization model to improve the resilience of UAV swarms under continuous attack is constructed, and the solution algorithm of the model is given. Finally, the feasibility and superiority of the model and algorithm are verified by simulation experiments.

Suggested Citation

  • Li, Hongxu & Sun, Qin & Zhong, Yuanfu & Huang, Zhiwen & Zhang, Yingchao, 2023. "A soft resource optimization method for improving the resilience of UAV swarms under continuous attack," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    • Handle: RePEc:eee:reensy:v:237:y:2023:i:c:s095183202300282x
    DOI: 10.1016/j.ress.2023.109368
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    References listed on IDEAS

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