In order to enhance recognition ability of enemy aircrafts in modern warfare process, with the characteristics of small amount of military aircraft samples and variety of shapes under different viewing conditions, the aircraft recognition algorithm combining center loss convolution neural network and ANN classifier is proposed. Firstly, five kinds of 6 000 aircraft images, which are produced by using 3Dmax software, is used to train the designed multi-layer CNN network model and the CNN features of these images are used to train ANN classifier. Next, the trained network model and classifier are used to forecast and classify the real aircraft samples, respectively. Finally, experimental results show that the recognition accuracy of the proposed algorithm to the five kinds of military aircraft can reach 97.17% in the case of small amount of aircraft samples and complex target shapes, which can prove that the algorithm is feasible to recognition of aircrafts type.