Abstract: The dictionary learning based radar high-resolution range profile(HRRP) target recognition method is proposed in this paper. The method can adaptively select the sparse decomposition coefficients based on the estimated test noise level. Compared with the traditional HRRP recognition methods, the proposed algorithm has a higher recognition rate and is more robust to the test noise environment. Furthermore, this method can obtain satisfactory performance even with the limited HRRP training samples from partial target-aspect angles (i.e., the training dataset is incomplete), thereby it can be used for HRRP dataset extension. The experiments based on measured HRRP data validate the proposed method.