According to the shortage of geometric moment nonorthogonality in obje ct description and the defect of continuous orthogonal moments in processing digital image with discretization er ror,in order to improve the recognition accuracy,this paper proposes a new aircraft type identification method with dis crete orthogonal Tchebichef moments combined with global and local features.Firs t of all,according to the relationship between the geometric moments and Tchebichef moments,the normalized geometric center moment and circular harmonic function are used to get rotation, scale and translation (RST) invariant radial-Tchebichef moments;Then,global and local features of aircraft target are extracted to form feature vector by the radial Tchebichef moments;Finally,four types of sample s et of the planes are constructed through Matlab program,the support vector machine (SVM) is used as classifier to identif y the aircraft type of test sample set which consists of the whole sample set except the training set,and the differ ences among geometric moment,Zernike moment and the proposed method are compared in recognition accuracy and the effect of t he training sample set size on the identification accuracy.Experimental results show that the proposed algorithm improves the rec ognition accuracy,and the recognition accuracy is still greater than 90% when the training sample set is small.