Abstract

Air to ground target optimal tracking has a great important for the ground target tracking of UAV. As the effects of ground target tracking by artificial neural networks are poor due to lots of shortcomings in the artificial neural networks, an ant colony optimization-support vector machine for air to ground target optimal tracking is proposed in this paper. Ant colony optimization is applied to select the appropriate parameters of support vector machine here. The experimental results show that the air to ground target tracking effects of ant colony optimization-support vector machine are better than support vector machine or BP neural network.

Paper Details