近海威胁目标威胁度评估与无人艇兵力分配  

Evaluation of Threat Degree of Offshore Threat Targets and Unmanned Vessel Force Distribution

作　　者：陈兴乐 黄炎焱[1] 陈天德 CHEN Xing-le;HUANG Yan-yan;CHEN Tian-de(School of Automation,Nanjing University of Science and Technology,Nanjing 210094,China)

机构地区：[1]南京理工大学自动化学院,南京210094

出　　处：《火力与指挥控制》2022年第3期73-81,共9页Fire Control & Command Control

基　　金：装备预研基金资助项目(315055106)。

摘　　要：针对近海防御战中威胁目标规模小、速度快、灵活性强的特点,为提高无人水面艇编队御敌的作战效能,及动态适应战场态势的复杂变化,提出近海威胁目标威胁度评估模型和无人艇调度分配方案。建立威胁度影响要素框架,设计各影响要素的效用函数,通过熵权法和TOPSIS算法得出威胁目标的威胁度,并对蚁群算法中的信息蒸发系数进行改进,基于威胁度使用改进的蚁群算法对威胁目标进行动态兵力分配。仿真结果表明:经过改进的蚁群算法在解决近海防御兵力分配问题时具有较好的动态实效性,提高了算法的全局搜索能力,在保证了一定收敛速度的同时避免了陷入局部最优。Aiming at the characteristics of small scale,fast speed,and strong flexibility of threat targets in offshore defense operations,in order to improve the combat effectiveness of unmanned surface vessel formations in defending against the enemy,and dynamically adapt to the complex changes in the battlefield situation,a threat evaluation model for offshore threat targets and unmanned surface vessel dispatching and distribution plan are proposed.A framework of threat degree influence factors is established,the utility function of each influence factor is designed,the threat degree of the threat targets through the entropy weight method and the TOPSIS algorithm is obtained,and the information evaporation coefficient in the ant colony optimization is improved,and based on the threat degree,the improved antcolony optimization is used to dynamically distribute forces to threat targets.The simulation results show that the improved ant colony optimization has better dynamic effectiveness in solving the problem of offshore defense force distribution,and can improve the algorithm’s global searching ability,and can avoid falling into local optimum while ensuring a certain convergence speed.

关 键 词：无人水面艇 威胁度评估 效用函数 兵力分配 蚁群算法 

分 类 号：TJ6[兵器科学与技术—武器系统与运用工程] TP15[自动化与计算机技术—控制理论与控制工程]