Research On UAV Discontinuous Area Detection And Threat Known Strike Mission Planning Methods

Unmanned aerial vehicles(UAVs)can carry out large maneuvering flights,and they can complete the strike or detection missions by carrying bombs or other loads,thus reducing unnecessary casualties and equipment losses.Sometimes,multiple UAVs need to be used together.Overlap between tasks in order to avoid the UAVs or interfere with each other,need to design a simple and effective method and algorithm for tasks reasonable ration fuels consumption,planning flight path,and implement multiple UAVs reasonable cover area task or goal,avoid collisions between UAVs,interference on our losses,improve the efficiency of the fleet,with smaller cost to complete the task as a whole.In this paper,combined with the practical application of UAVs,the complex UAVS task is simplified into the detection task model with unknown target and the attack task model with known target,and the task relevance is proposed.The detection task is regarded as a traversal problem and the combat task as an optimal path problem between two points.The threat model of air defense weapon to UAV is analyzed,and the environment model based on the improved Voronoi diagram is established.The cost of different missions is studied,the cost model is established,which is composed of threat cost and voyage cost,and the "distance weighting factor" is proposed to balance the threat cost and voyage cost.Improved Ant Colony Algorithms for Optimal Solutions of the least costly task allocation and path planning scheme.Two methods of task allocation,namely slope greedy and distance greedy,are proposed to detect multi-machine and multi-task nodes.Finally,the simulation data show that the proposed method and improved algorithm are simple,effective and feasible,and can be applied to UAV mission planning.