An aircraft formation recognition method based on deep learning

Abstract

Aircraft formation recognition is of great significance in the intention prediction and the threat assessment field, but the current traditional template-based methods need to manually extract features and construct templates, which has the problems of complex process and poor effect. This paper proposes a formation recognition method based on GAN and CNN, which can perform end-to-end formation recognition. First, a GAN model is designed to generate a large amount of new aircraft formation data from a small amount of measured data. Then a CNN-based aircraft formation recognition model is designed. After the model training is completed, the aircraft formation recognition can be completed by inputting the measured aircraft formation data. The experimental results show that this method can improve the recognition accuracy by 8%.