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Task allocation plays an important role in unmanned combat aerial vehiclespsila (UCAVs) cooperative control. In order to solve the problem of multiple UCAVspsila cooperative task allocation, an improved ant colony algorithm (ACA) is proposed. On the basis of modeling cooperative multiple task assignment problem, the application of improved ACA is discussed. Cooperative task allocation for UCAVs shows a property of dynamic multiple phased decision problems and a task tree is used to represent that case. In the improved ACA, pheromone change is very different from other classic improved ACA. Especially when pop-up targets appear, with the help of changed pheromone matrix which is gained from former iterations, it becomes easier and quicker to find good solutions.