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Multi-UAV Cooperative Anti-Submarine Search Based on a Rule-Driven MAC Scheme
1College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116000, China
2College of Mechanical and Electrical Engineering, Dalian Minzu University, Dalian 116000, China
*Author to whom correspondence should be addressed.
Academic Editor: Seong-Ik Han
Appl. Sci. 2022, 12(11), 5707; https://doi.org/10.3390/app12115707
Received: 13 May 2022
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Revised: 28 May 2022
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Accepted: 31 May 2022
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Published: 3 June 2022
(This article belongs to the Section Aerospace Science and Engineering)
In order to enhance the anti-submarine capability of multi-unmanned
aerial vehicles (multi-UAVs) in the unknown sea environment and improve
the search efficiency, in this paper, we propose a
rule-inspired-multi-ant colony (RI-MAC)-based UAV cooperative search
algorithm. First, a special sea area anti-submarine search model is
established, including an association rule-driven target probability map
(TPM) model, a UAV kinematics model, and a sensor model. The novel
model has the characteristics of rule linkage, which effectively
improves the accuracy of target detection probability in unknown
environments. Secondly, according to the established search model, a
multi-objective utility function based on association rules is derived.
In order to solve the problem of multi-objective optimization, an RI-MAC
algorithm based on association rules is proposed, and a pheromone
update method using threat avoidance is designed to optimize the search
path of multi-UAVs. Finally, a simulation experiment is conducted to
verify the effectiveness and superiority of the proposed search
algorithm.
Keywords:
association-driven probability map; collaborative search; rule-inspired multi-ant colony algorithm
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