一种改进蚁群算法的无人机避险方法仿真研究

Simulation study of UAV conflict resolution based on an improved ant colony algorithm

随着低空空域的逐渐开放以及无人机产业的高速发展,无人机数量不断上升,无人机间随时有发生冲突的可能,需要一种可靠的冲突解脱技术使无人机可以避免危险。针对无人机冲突解脱问题,提出基于改进蚁群算法的无人机冲突解脱方法:采用参数自适应调整策略,根据解的质量,动态调整参数值,防止算法早熟,提高收敛精度;在算法状态转移规则中引入扰动因子,加快算法初期收敛。算法测试实验结果显示,改进蚁群算法收敛精度更高。仿真实验表明,改进算法可以帮助两无人机及时脱离危险。该算法作为一种通用优化算法,也可应用到目标识别、路径规划等问题中,具有重要的研究意义与广泛的应用价值。

With the gradual opening of the low-altitude airspace and the rapid development of Unmanned Aerial Vehicle(UAV)industry,the users of UAV are increasing continuously and the conflicts could occur at any time.It is necessary to develop a reliable UAV conflict resolution algorithm to avoid the danger.This paper proposes an UAV conflict resolution algorithm based on the improved ant colony algorithm with two advantages.Firstly,the algorithm adopts adaptive parameters adjustment strategy,which adjusts the parameters value dynamically according to the quality of the solution,prevents the algorithm premature convergence and improves the accuracy.In addition,the disturbance factors is introduced to the state transition rules of random selected path in order to accelerate the initial convergence.The simulation results have shown that the improved algorithm displays obvious superiority in convergence precision,helping the two UAVs avoiding dangers in time.The algorithm described in this paper could be applied to target identification,path planning and other issues as a general optimized algorithm,which is of great significance and wide application.