Abstract: The classification of small and micro targets at low altitude is one of the difficult problems in radar field, which seriously effects the detection performance of radar and the effectiveness of system combat command. In order to accurately and quickly identify small and micro targets at low altitude such as rotors, fixed wings and vehicles, a classification and recognition method of small and micro targets of low-resolution radar based on high-dimensional feature domain is proposed in this paper. A series of time-frequency micro features and track macro features are extracted from the signal layer, and high-dimensional feature domain is obtained by internal product and power transformation of features. A multi-level target classification and recognition model is established by using learning tree network to realize the classification and marking of small and micro targets at low altitude. The results show that this method can classify small and micro objects accurately and quickly.