Application of Improved Ant Colony Algorithm in Flight Path Planning

In this paper, a new improved ant colony algorithm is proposed, which solves the problems of local optimization and premature stagnation when the traditional algorithm is applied to flight path planning. By describing the path planning problem, the mathematical model of path planning in the intelligent guidance of aircraft is built, and the known terrain and threat information in the flight area are integrated to reduce the data space. Based on the dynamic constraints of aircraft flight, a constraint model including maneuverability constraints and external threat constraints is built and integrated into the terrain information. The intelligent guidance path is planned by constructing a path synthesis cost function that satisfies the kinematics of the aircraft. The ant colony algorithm is selected from the modern heuristic algorithm and improved. Simulation results show that the algorithm can avoid terrain obstacles effectively, has the lowest comprehensive cost, meets the requirements of maneuverability and spatial accessibility, and basically achieves the expected goal.