Aiming at the problem that the Sage-Husa adaptive Kalman filter algorithm is easy to diverge and is sensitive to the selection of initial conditions, an adaptive strong tracking algorithm based on Sage-Husa adaptive Kalman filter algorithm is proposed. The algorithm starts from the Sage-Husa adaptive Kalman filter algorithm and introduces the strong tracking technology in it. By online modifying the one-step prediction error covariance matrix with fading factor, the algorithm can cope with the uncertainties such as scene changes, and has stronger robustness. By improving the Sage-Husa adaptive algorithm, the noise covariance matrix is estimated online in real time, so that the algorithm is adaptive to noise changes and has better tracking accuracy. Simulation results show that the proposed filter method can effectively improve the tracking accuracy and robustness of the carrier tracking loop.