摘要
在潜艇遭遇鱼雷攻击进行机动规避的过程中,针对潜艇防御鱼雷时水声对抗器材的优化配置问题,研究了一种典型的反鱼雷对抗策略,并建立了对抗过程中相关实体的运动及水声探测模型,在此基础上将粒子群算法用于对抗过程中四个决策变量的智能整定,对使用水声对抗器材与潜艇的规避有机结合的对抗策略进行合理优化,结合蒙特卡洛法对算法进行设计和仿真。通过比较,采用粒子群算法的反鱼雷对抗策略可以提高潜艇的生存概率,对研究水下作战中潜艇防御鱼雷具有实际的参考意义。
When the submarine was attacked by torpedo and in the mean time it had to properly maneuver, due to the optimal allocation problem for the acoustic warfare equipment, a typical anti-torpedo counterplan was studied, the movement and water acoustic detection models in the course were built, and on this base, the particle swarm optimization （PSO） algorithm was applied in the intelligent tuning of the four controller parameters, so as to optimize the counterplan reasonably which used acoustic warfare equipments and submarine evasion, then combined with the Monte Carlo method, algorithm was design and simulation was conducted. By comparison, it can greatly improve the survival probability of the submarines by using the strategy that PSO algorithm is adopted, which has practical significance to defense torpedo for the submarine in the undersea warfare.
出处
《系统仿真学报》
CAS
CSCD
北大核心
2012年第9期2023-2026,共4页
Journal of System Simulation
基金
船舶预研支撑技术基金(11J4.1.1)
关键词
反鱼雷
粒子群
蒙特卡洛
水声对抗
anti-torpedo
particle swarm optimization
Monte-Carlo
acoustic warfare
