异构无人机编队防御及评估策略研究

Study on Heterogeneous UAV Formation Defense and Evaluation Strategy

无人机编队对抗问题一直是科学研究的一个热点,但针对无人机群防御部署问题的相关研究较少。文中以防御型无人机对普通无人机(如民用、商用、侦查、巡航、勘探)的保护问题为背景,对已有的异构无人机编队的编码解码方案进行改进。从导弹飞行距离和非武装无人机的安全两个方面建立适应度函数,使用遗传算法对无人机防御编队进行优化。针对不同规模和不同队形的敌机编队,对我方无人机编队进行优化。求解结果表明,在不同的敌机编队中,遗传算法均能在30次迭代内以较快速度收敛于最优值,并给出相应的优化队形。最后通过概率效果评估,绘制了5种战况损失曲线,可以看出所设计的防御部署战略是有效的,我方无人机最大损失数量为6,最小损失数量为0,平均损失数量为3,平均损失率为18.75%。该方法对异构无人机群的防御部署研究具有一定的参考价值。

The problem of UAV formation confrontation has always been a hot topic in scientific research,and there are few related studies on the deployment of UAV group defense.Based on the protection of defensive UAV against common UAV,such as civil,commercial,reconnaissance,cruise and exploration,the coding and decoding scheme of existing heterogeneous UAV formation is improved.The fitness function is established from the missile flight distance and the safety of unarmed drones,and the genetic algorithm is used to optimize the defense formation of the drone.According to the situation of enemy UAV of different sizes and various formations,the formation of our UAV is optimized.The solution results show that the genetic algorithm can converge to the optimal value in different enemy formations at a high speed within 30 iterations,and the corresponding optimized formation is given.Finally,by evaluating the probability effect and drawing the loss curve of five combat situations,it can be seen that the defense deployment strategy designed in this paper is effective.The maximum loss quantity of our UAVs is 6,minimum loss quantity is 0,average loss quantity is 3,and average loss rate is 18.75%.This method is of great significance for the research of UAV group defense deployment.