多目标时空同步协同攻击无人机任务分配与轨迹优化

针对复杂战场环境下分布式无人机对多目标协同打击任务，提出多目标攻击的任务分配与轨迹优化算法。建立典型多目标打击的任务场景和无人机模型；基于Delaunay三角形理论，以禁飞区为节点构建搜索地图；运用A^*算法实现威胁最小的单机路径搜索；在无人机动力学约束和能耗损失最小的基础上，引入时间调节因子，采用基于贝塞尔曲线的分布式无人机时空同步轨迹优化方法，得到对多目标同时打击的优化轨迹；设计轨迹跟踪控制器，对预规划轨迹进行跟踪仿真。仿真结果表明，多目标攻击的任务分配与轨迹优化方法能够对多目标实现多角度、时空同步、分布式协同打击，且对噪声及阵风等具有较强的抗干扰能力。

Task Allocation and Trajectory Optimization of UAV for Multi-target Time-space Synchronization Cooperative Attack

A task allocation and trajectory optimization algorithm for multi-target attack is proposed for the coordinated attack task of distributed UAVs attacking multiple targets in a complex battlefield environment. The typical multi-target strike mission scenarios and UAV models are established. A search map with no-fly zones as nodes is constructed based on Delaunay triangle theory. A^* algorithm is used to achieve the least threatening single-aircraft path search. In terms of UAV dynamics constraints and minimum energy loss, the time adjustment factor is introduced and the distributed UAV time-space synchronization trajectory optimization method based on Bezier curve is adopted to obtain the optimized trajectory for simultaneous attack on multiple targets. A trajectory tracking controller was designed for simulation track of pre-planned trajectory. The simulated results show that the proposed multi-target attack task allocation and trajectory optimization method can achieve multi-angle, time-space synchronization, and distributed coordinated attack on multiple targets, and it has strong robustness against interference such as noise and wind gusts.