Multi-UAV Cooperative Anti-Submarine Search Based on a Rule-Driven MAC Scheme

Abstract

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.