Weapon-target assignment in UAV cluster based on pheromone heuristic wolf pack algorithm

被引：0
|
作者：
Liu S. [1 ]
Wang H. [1 ]
Yu N. [1 ]
Hao L. [1 ]
机构：
[1] PLA Troop 66133, Beijing
来源：
Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics | 2021年 / 47卷 / 02期
关键词：
Ant Colony Optimization (ACO) algorithm; Pheromone heuristic rules; Unmanned Aerial Vehicle(UAV); Weapon-Target Assignment(WTA); Wolf Pack Algorithm(WPA);
D O I：
10.13700/j.bh.1001-5965.2020.0208
中图分类号：
学科分类号：
摘要：
Unmanned Aerial Vehicle (UAV) cluster operation is an important mode of intelligent warfare in the future. In order to give full play of the overall operational advantages of UAV cluster, a mathematical model is constructed to solve the Weapon-Target Assignment (WTA) problem in UAV cluster attacks and obtain the optimal scheme. The constraints of mission completion, effective killing and attack consumption are established in the model, which can meet the requirements of the mission, and also save the consumption of UAV combat units to maintain the power of UAV cluster. The improved Wolf Pack Algorithm (WPA) with scouting and summoning operators is used to solve the model. To obtain the higher global optimization efficiency and avoid trapping in local optimum, the weapon-target assignment in UAV cluster attack based on Pheromone Heuristic Wolf Pack Algorithm (PHWPA) is proposed to improve WPA's scouting behavior and renewable mechanism by using pheromone heuristic rules from Ant Colony Optimization (ACO). The simulation results show that the proposed method is effective. Compared with several algorithms, PHWPA has more efficient search ability. The proposed method can provide support for firepower planning of UAV cluster. © 2021, Editorial Board of JBUAA. All right reserved.
引用
收藏
页码：297 / 305
页数：8
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