Route Planning of UAV Based on Improved Ant Colony Algorithm

Abstract

On the basis of analyzing the tactical characteristics and the mission requirements of UAV, a route planning model is established, which is composed of a comprehensive threat model, a performance constraint model and a mission effectiveness model. A dual population genetic ant colony algorithm is designed, with which dual population ant colony can be searched and iterated independently at same time. In the iterative process, bidirectional dynamic adjust adaptively the volatile coefficient of the pheromone which is limited within a certain range. This algorithm can avoid local optimum and stagnation in the search and iteration. Finally The improved ant colony algorithm is applied to the route planning of UAV, and the feasibility and effectiveness of this method is verified by simulation.