在战场复杂电磁环境下，保证蜂群无人机编队机间飞行安全和编队内可靠通信尤为重要。本文提出一种蜂群无人机编队内无线紫外光协作避让算法，结合无线紫外光覆盖特点设计紫外虚拟围栏避让策略，基于增强矢量场直方图法针对无人机在避让时的运动状态的代价函数进行改进，采用无迹卡尔曼预测器预测邻近无人机的飞行状态。在两种预测场景下的避让仿真中，结果表明，与增强矢量场直方图法进行对比，本文算法的整体运动轨迹平滑，局部避让时无明显抖动，避让路径总长度平均减少3.46%，总耗时平均减小18.94%，验证了蜂群无人机编队内无线紫外光协作避让算法的有效性。

For complex battlefield environments, it is especially important to ensure the safety of flight between uninhabited aerial vehicles (UAV) formations and reliable communication within the formation. This paper proposes an algorithm for collaborative avoidance using wireless ultraviolet light between drones in a bee colony drone formation. Combined with the above algorithm and using the characteristics of wireless ultraviolet light coverage, the avoidance strategy of ultraviolet virtual fence is designed. And by enhancing the vector field histogram method to improve the cost function of the state of motion of the drone when performing mutual avoidance. In addition, the algorithm uses the unscented Kalman filter to predict the flight status of nearby uninhabited aerial vehicles. The simulation results show that in the avoidance simulations of the two prediction scenarios, the overall motion trajectory of this algorithm is smoother than that of the enhance vector field histogram method. At the same time, there is no obvious jitter when local avoidance occurs, the total length of the avoidance path is reduced by 3.46% on average, and the total time consumption is reduced by 18.94%. This verifies that the wireless ultraviolet cooperative avoidance algorithm in a bee colony drone formation is effective.