Uav Route Planning Based On Ant Colony Algorithm

The ant algorithm is one kind of burgeoning optimization algorithm. Based on ant algorithm basic principle, this article lies a strong emphasis on advantage and disadvantage of many kinds of basic ants algorithm (Ant System with elitist strategy, Rank-Based Version of System, Ant Colony System, Max-Min Ant System, Best-Worst Ant System). In the paper, the original ant colony algorithm is improved, and the measure of adaptively adjusting pheromone are applied, In allusion to characteristic of UAV route planning, the battlefield model is established in the flight area of UAV , using the suitable UAV route performance index, holding the improved ant algorithm is applied in UAV route planning. The paper takes the orientative point of UAV entering the enemy defensive area as the initial station, the campaign/the tactical attack goal location as the target point. It connects the initial station and the target point through carrying on the grid division to the planning space to forming network chart. The node of the network chart is defined as UAV feasible way node, in the algorithm, which is choosing node during the act process of ant. Through the probability choice function the best feasible spots are determined, forming a most superior route. This algorithm can find better path at higher convergence speed, and solve UAV route planning well. The paper finally carries on the algorithm simulation, using the Matlab language to the model of UAV route planning. The result shows that the algorithm is reasonable validity and the feasibility.