Aiming at the problems that accurate motion tracking of infrared object is hard in complex background by using a single algorithm,a new infrared object tracking method which combines scale unscented Kalman filter(SUKF) and scale invariant feature transform(SIFT) is proposed.Firstly,SUKF can estimate the state of unknown system,and the position of object center is located,and then the local detection area with SIFT feature is identified.Secondly,the features of object are obtained and matched by SIFT algorithm in this local area.Finally,the object center is accurately located by SIFT algorithm,and the state model of SUKF is updated and corrected by the final location.Compared with the related methods,the proposed tracking strategy based on SUKF-SIFT has better tracking results and real-time performance.