In order to solve tracking problem of maneuvering target in nonlinear background, an Augmented Interacting Multiple Model Cubature Kalman Filter (AIMMCKF) algorithm is put forward. To obtain the fixed-lag smoothing state estimation, IMMCKF approach is applied to a nonlinear state-augmented system in the proposed algorithm. At the same time, to tackle different models problem within being represented in different state spaces, corresponding augmented conversion operation can be used. The simulation results show that, the proposed algorithm achieves higher precision and stronger adaptability for maneuvering target tracking in comparison with traditional nonlinear tracking algorithms.