静态威胁下的无人机航迹规划

摘要

TheUAV(UninhabitedAirVehicle),duingtoitsadvantages,hasbeenwidelyusedin military and civilian fields.The essential of the UAV path planning is optimization for multi -objective and multi-constraint.This article introduces the crucial theory of the UAV path planning.The neural network algorithm is used to set models for the fired and non-fired threats in a static environment and the genetic algorithm is used for UAV path planning.The superiority of the algorithm is verified by simulation of different environment models.%无人机（Uninhabited Air Vehicle，UAV）由于其自身优点，已经在军事以及民用领域取得广泛使用。无人机的航迹规划本质可归结为一个多目标多约束条件的最优化问题。简单介绍无人机航迹规划的基本理论。运用神经网络算法针对静态环境下的火力威胁和非火力分别建模。运用遗传算法对无人机进行航迹规划。通过建立不同环境的模型仿真验证算法的优越性。