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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2023, Vol. 44 ›› Issue (11): 327561-327561.doi: 10.7527/S1000-6893.2022.27561

• Electronics and Electrical Engineering and Control • Previous Articles     Next Articles

Distributed cooperative area search method for UAV swarms based on revisit mechanism

Chao WEN1, Wenhan DONG2, XIE Wujie2, Ming CAI2(), Ri LIU3   

  1. 1.Graduate School,Air Force Engineering University,Xi’an 710038,China
    2.College of Aeronautical Engineering,Air Force Engineering University,Xi’an 710038,China
    3.Department of Theory Training,Air Force Harbin Flight Academy,Harbin 150000,China
  • Received:2022-06-01 Revised:2022-06-30 Accepted:2022-09-29 Online:2023-06-15 Published:2022-10-14
  • Contact: Ming CAI E-mail:caiming1124@sina.com
  • Supported by:
    Basic Research Project in Natural Science of Shaanxi Province(2022JQ-584)

Abstract:

To enable Unmanned Aerial Vehicle (UAV) swarms to search for the dynamic targets efficiently in an unknown mission area while maximizing coverage of search, this paper proposes a Revisit Mechanism-driven Distributed Cooperative Search Decision (RM-DCSD) algorithm for UAV swarms. Firstly, a comprehensive situational information map model with three attributes and its updating mechanism are constructed based on the gridding method, laying the foundation for the UAV to make real-time online search decisions. Secondly, to maximize search efficiency and take into account the flight safety and energy cost of the UAV, a UAV search effectiveness function is established. On this basis, a UAV local finite-time domain rolling optimization model is constructed based on the thought of rolling optimization. Thirdly, considering the actual search demand for moving targets as well as the false alarm and missed detection of sensors, a pheromone-guided revisit mechanism and a weight coefficient dynamic switching-guided revisit mechanism are designed respectively. Then, drawing on the thought of distributed model predictive control, a distributed cooperative search decision mechanism for UAV swarms based on information fusion is designed, which achieves decoupled update of the situational information maps of UAV members on the basis of ensuring the distributed cooperative optimal decision of swarms, and further enhances the system robustness. Finally, the effectiveness of the proposed algorithm is verified by numerical simulation experiments. The results show that RM-DCSD performs good adaptability to dynamic unknown search environments, and can effectively consider the search requirements of ground moving targets through the revisit mechanisms while enabling UAV swarms to maximize coverage of search for unknown areas.

Key words: UAV swarm, cooperative area search, revisit mechanism, distributed model predictive control, information fusion

CLC Number: