基于改进蚁群算法的无人机冲突解脱技术

Key Technology in Multi UAV Conflict Detection and Resolution Strategy

基于ADS B监视数据,提出了一种基于线性外推法的机载无人机冲突探测与解脱方法,为可能发生的冲突提供预警。为解决多无人机冲突问题,引入基本蚁群算法,并通过加入速度调整策略来优化传统的基本蚁群算法的冲突简化模型。提出了一种基于速度调整策略和航向调整策略的多无人机冲突解脱方案。通过加入排序系统和角度信息,改进了蚁群算法。结果表明,改进的蚁群算法可为空域内多无人机规划无人机冲突解脱路径。改进后的蚁群算法,提高了计算效率,收敛出最优化目标所需时间减少了43.9%,且最终总延误距离减少了58.4%。

Based on ADS-B surveillance data,this paper proposes a multi-unmanned aerial vehicle(multi-UAV)collision detection method based on linear extrapolation for ground-based UAV collision detection and resolution,thus to provide early warning of possible conflicts.To address the problem of multi-UAV conflict,the basic ant colony algorithm is introduced.The conflict simplification model of the traditional basic ant colony algorithm is optimized by adding a speed regulation strategy.A multi-UAV conflict resolution scheme is presented based on speed regulation and heading strategies.The ant colony algorithm is improved by adding angle information and a queuing system.The results show that the improved ant colony algorithm can provide multi-UAV joint escape routes for a multi-UAV conflict situation in airspace.Unlike the traditional ant colony algorithm,our approach converges to the optimization target.The time required for the calculation is reduced by 43.9%,and the total delay distance caused by conflict resolution is reduced by 58.4%.