Aiming at the suppression of enemy air defense(SEAD)task under the complex and complicated combat sce-nario,the spatiotemporal cooperative path planning methods are studied in this paper.The major research contents in...Aiming at the suppression of enemy air defense(SEAD)task under the complex and complicated combat sce-nario,the spatiotemporal cooperative path planning methods are studied in this paper.The major research contents include opti-mal path points generation,path smoothing and cooperative rendezvous.In the path points generation part,the path points availability testing algorithm and the path segments availability testing algorithm are designed,on this foundation,the swarm intelligence-based path point generation algorithm is utilized to generate the optimal path.In the path smoothing part,taking ter-minal attack angle constraint and maneuverability constraint into consideration,the Dubins curve is introduced to smooth the path segments.In cooperative rendezvous part,we take esti-mated time of arrival requirement constraint and flight speed range constraint into consideration,the speed control strategy and flight path control strategy are introduced,further,the decoupling scheme of the circling maneuver and detouring maneuver is designed,in this case,the maneuver ways,maneu-ver point,maneuver times,maneuver path and flight speed are determined.Finally,the simulation experiments are conducted and the acquired results reveal that the time-space cooperation of multiple unmanned aeriel vehicles(UAVs)is effectively real-ized,in this way,the combat situation suppression against the enemy can be realized in SEAD scenarios.展开更多
针对动态不确定战场环境下多无人机对多区域、多目标的协同察打任务规划过程中存在的信息不确定、任务多约束及航迹强耦合的多目标优化与决策问题,结合Dubins航迹规划算法,提出了一种融合多种改进策略的灰狼优化算法(grey wolf optimiza...针对动态不确定战场环境下多无人机对多区域、多目标的协同察打任务规划过程中存在的信息不确定、任务多约束及航迹强耦合的多目标优化与决策问题,结合Dubins航迹规划算法,提出了一种融合多种改进策略的灰狼优化算法(grey wolf optimization algorithm incorporating multiple improvement strategies,IMISGWO).首先,针对动态环境带来的无人机巡航速度及察打任务消失时间的不确定性,基于可信性理论建立了以最大化任务收益为指标的任务规划数学模型;其次,为实现该问题的快速求解,设计了初始解均匀分布、个体通信机制调整、动态权重更新和跳出局部最优等策略,提升算法解搜索能力;最后,构建了多无人机察打一体典型任务仿真场景,通过数字仿真以及虚实结合半实物仿真试验验证了算法的可行性和有效性.仿真结果表明:算法在求解不确定环境下耦合航迹的多无人机察打一体任务规划问题时,能够生成多机高效的任务执行序列和满足无人机飞行性能约束的飞行轨迹,且能够适用于无人机数量增加导致问题复杂度增加情形下此类问题的求解.展开更多
With the development of technology, the relevant performance of unmanned aerial vehicles(UAVs) has been greatly improved, and various highly maneuverable UAVs have been developed, which puts forward higher requirement...With the development of technology, the relevant performance of unmanned aerial vehicles(UAVs) has been greatly improved, and various highly maneuverable UAVs have been developed, which puts forward higher requirements on target tracking technology. Strong maneuvering refers to relatively instantaneous and dramatic changes in target acceleration or movement patterns, as well as continuous changes in speed,angle, and acceleration. However, the traditional UAV tracking algorithm model has poor adaptability and large amount of calculation. This paper applies support vector regression(SVR)to the interacting multiple model(IMM) algorithm. The simulation results show that the improved algorithm has higher tracking accuracy for highly maneuverable targets than the original algorithm, and can adjust parameters adaptively, making it more adaptable.展开更多
文摘Aiming at the suppression of enemy air defense(SEAD)task under the complex and complicated combat sce-nario,the spatiotemporal cooperative path planning methods are studied in this paper.The major research contents include opti-mal path points generation,path smoothing and cooperative rendezvous.In the path points generation part,the path points availability testing algorithm and the path segments availability testing algorithm are designed,on this foundation,the swarm intelligence-based path point generation algorithm is utilized to generate the optimal path.In the path smoothing part,taking ter-minal attack angle constraint and maneuverability constraint into consideration,the Dubins curve is introduced to smooth the path segments.In cooperative rendezvous part,we take esti-mated time of arrival requirement constraint and flight speed range constraint into consideration,the speed control strategy and flight path control strategy are introduced,further,the decoupling scheme of the circling maneuver and detouring maneuver is designed,in this case,the maneuver ways,maneu-ver point,maneuver times,maneuver path and flight speed are determined.Finally,the simulation experiments are conducted and the acquired results reveal that the time-space cooperation of multiple unmanned aeriel vehicles(UAVs)is effectively real-ized,in this way,the combat situation suppression against the enemy can be realized in SEAD scenarios.
基金supported by the Foundation of Key Laboratory of Near-Surface。
文摘With the development of technology, the relevant performance of unmanned aerial vehicles(UAVs) has been greatly improved, and various highly maneuverable UAVs have been developed, which puts forward higher requirements on target tracking technology. Strong maneuvering refers to relatively instantaneous and dramatic changes in target acceleration or movement patterns, as well as continuous changes in speed,angle, and acceleration. However, the traditional UAV tracking algorithm model has poor adaptability and large amount of calculation. This paper applies support vector regression(SVR)to the interacting multiple model(IMM) algorithm. The simulation results show that the improved algorithm has higher tracking accuracy for highly maneuverable targets than the original algorithm, and can adjust parameters adaptively, making it more adaptable.
