This paper proposes a sequential filtering target tracking algorithm based on the converted measurement cubature Kalman filter to solve the problem of Doppler-assisted target tracking. Firstly, a new measurement function is reconstructed by decorrelating the range measurement error with Doppler measurement error. Then, based on the Bayesian method, the unified theoretical framework of the sequential processing algorithm with Doppler measurement is proposed, and the sequential filtering of range measurement and Doppler measurement is realized. Under this framework, the new sequential filtering target tracking algorithm based on the converted measurement cubature Kalman filter is proposed. In this algorithm, the target state is estimated by the converted cubature Kalman filter and position measurement, and then the final state estimation is a combination of pseudo-Doppler measurement estimation and the measurement update of classical cubature Kalman filter. By analyzing the performance of the proposed algorithm, it is proved that the algorithm has good consistency and convergency. Simulation results show that this algorithm has higher tracking accuracy than other tracking algorithms.