In view of the deficiency of basic ant colony algorithm in UAV autonomous track planning,which is easily trapped in local optimal solution,the elite ant colony algorithm with improved guidance factors was adopted to study the global track planning of UAV in two-dimensional space environment.Grid method was selected to divide the space,static obstacle map was established and heuristic factor was constructed.Elite ant colony algorithm with improved guidance factor was used to find the shortest track to reach the target point.Finally,through simulation experiment,the track of elite ant colony algorithm with improved guide factor is compared with that of basic ant colony algorithm and maximum and minimum ant colony algorithm.