To overcome the shortcomings of traditional nonlinear filtering algorithms, i.e., the EKFs tracking accuracy decreases rapidly at high maneuvering and low data rate, and UKF has small linearization error but poor real-time performance at low data rate, an interactive multi-model filtering algorithm based on data rate control is proposed.This algorithm adaptively allocates the weights of EKF and UKF according to the target detection rate and the system non-linearity in different combat modes, which effectively overcomes the shortcomings of only using one filtering model in previous algorithms.The simulation results show that the proposed algorithm solves the problem that the tracking accuracy and stability of the system decrease too fast when the data rate of the EKF algorithm decreases while the target is maneuvering.Compared with that of the UKF algorithm, the running time of the proposed algorithm is greatly shortened and the radar resource consumption is reduced when the tracking accuracy of the system decreases little in the maneuvering phase.