Precise point positioning (PPP) technology has been widely used in many fields because of its simple operation and high positioning accuracy. Aiming at the observation noise and multipath effect that may be caused by the change of surrounding environment, the traditional filtering algorithm cannot solve the problem of precision decline caused by it, this paper proposes a strong tracking adaptive Kalman filtering (SAKF) algorithm. The fading factor is introduced to adjust the prediction error value, and the measurement noise covariance is reconstructed by IGGⅢ function method, to achieve realize PPP solution. The experimental results show that the positioning accuracy of SAKF is improved by about 20% compared with the traditional algorithm in static solution, and it is improved by about 55% ~ 60% in quasi-dynamic solution, and it has better convergence stability.