Aiming at the maneuvering multi-target tracking problem with unknown or time-varying number of targets in the nonlinear Gaussian condition, an unscented Kalman probability hypothesis density filter based on the interactive multiple model is proposed.Firstly, combining with the implementation mechanism of state prediction and measurement update in the unscented Kalman filter, the unscented Kalman probability hypothesis density filter for the nonlinear Gaussian system is constructed in the framework of the Gaussian mixture probability hypothesis density filter.On this basis, the motion pattern uncertainty in the target maneuvering system is solved by utilizing the soft decision mechanism of the state model in the interactive multiple model algorithm.Theoretical analysis and simulation results verify the feasibility and effectiveness of the proposed algorithm.