关键词: 主动声呐浮标, 布阵优化, 潜艇, 多目标粒子群优化算法, 反潜

Abstract: Active sonar buoy is widely used as a submarine detection equipment for anti-submarine aircraft. It is of great significance to study its array optimization method to quickly and effectively complete anti-submarine combat tasks and improve the efficiency of anti-submarine combat. Aiming at the problem that the submarine position distribution model and the active sonar buoy search range are simplified in the existing research, it is difficult to meet the needs of the actual scene. The distribution law model of the submarine under the condition of known general heading and unknown speed and the evaluation model of the active sonar buoy array search efficiency based on the active sonar equation and the grid method are established. By introducing Kent map, dynamically adjusted inertia weight and learning factor, a buoy array optimization method based on improved multi-objective particle swarm optimization algorithm is proposed. The simulation verification is carried out in the scene of on-call submarine search. The simulation results show that the proposed algorithm can obtain the optimal deployment scheme in different scenarios, which proves the feasibility and effectiveness of the algorithm. Compared with other algorithms, the algorithm proposed in this paper has a larger search probability and a shorter computation time under the same delivery amount, which proves the superiority of the algorithm.

Key words: active sonobuoy, array optimization, submarine, multi-objective particle swarm optimization, anti-submarine