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Acta Aeronautica et Astronautica Sinica ›› 2024, Vol. 45 ›› Issue (S1): 730773.doi: 10.7527/S1000-6893.2024.30773

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Optimised Harris hawks multi-UAV dynamic target search with fused infographics

Ting LIU1(), Guoxin ZHOU1, Yang XU2, Delin LUO3,4, Zhengyu GUO5, Mengjie YANG6   

  1. 1.College of Aeronautical Engineering,Jilin Institute of Chemical Technology,Jilin 132022,China
    2.School of Civil Aviation,Northwestern Polytechnical University,Xi’an 710072,China
    3.School of Aerospace Engineering,Xiamen University,Xiamen 361102,China
    4.National Key Laboratory of Air-based Information Perception and Fusion,Luoyang 471000,China
    5.China Airborne Missile Academy,Luoyang 471000,China
    6.Sheng Yun Technology Co. Ltd. ,Kunming 650000,China
  • Received:2024-06-03 Revised:2024-08-02 Accepted:2024-08-19 Online:2024-08-27 Published:2024-08-26
  • Contact: Ting LIU E-mail:liuting@jlict.edu.cn
  • Supported by:
    National Key Laboratory of Air-based Information Perception and Fusion and the Aeronautic Science Foundation of China(20220001068001);Natural Science Basic Research Plan in Shanxi Province of China(2023-JC-QN-0733);Yunnan Province Science Technology Talent and Platform Plan (Academician Expert Workstation)(202305AF150152)

Abstract:

In the study of cooperative search for moving targets by multi-Unmanned Aerial Vehicle (multi-UAV), this paper proposes a cooperative search decision-making method that integrates an information graph model with the optimized Harris hawk optimization algorithm. A target probability information graph model based on Gaussian distribution is constructed, which enhances the certainty of target existence probability in the environment through the establishment of a certainty information graph model. Furthermore, a digital information pheromone graph with attraction and repulsion mechanisms is used to guide UAVs to move towards unexplored areas, effectively reducing repetitive search behaviors and enhancing the efficiency of cooperative search. To address the issue of Harris hawk optimization algorithm being prone to local optima, a non-linear energy factor updating strategy is proposed, integrating the optimal individual positions and presenting a new position update formula. Finally, to search for the targets with randomly changing trajectories, a revisitable digital information graph and an adaptive target search gain function are designed to enhance the capability of UAVs to capture moving targets. Simulation results verify the effectiveness of the improved Harris hawk optimization algorithm in cooperative search for moving targets by multiple UAVs.

Key words: multi-UAV, cooperative search, moving target, distributed, enhanced Harris hawks algorithm

CLC Number: