Aiming at the problem that the traditional ant colony algorithm has long search time and is easy to fall into local optimal solution in UAV 3D route planning, an improved ant colony algorithm strategy is proposed. The performance constraints of the fixed-wing UAV are used to judge whether the node to be expanded is feasible or not, which reduces the amount of calculation and the search time of the algorithm. The height planning of the waypoint is directly set, which simplifies the 3D route planning problem into a 2D route planning problem and reduces the complexity of the algorithm. The global pheromone update rule and the safety heuristic factor are improved to solve the problems of local optimal solution and threat source evasion. The simulation results show that compared with the traditional ant colony algorithm, the improved ant colony algorithm can effectively plan a flight route from the starting point to the end point, and has higher effectiveness and practicability.