Aiming at the low accuracy of Beidou pseudo ranges that is caused by some noises with unknown reason or inaccurate statistical characteristics, and in order to reduce the influence of state estimation on filtering process because of the inaccuracy of statistical characteristics of noises, a new method of positioning calculation that unscented Kalman filter (UKF) combines with noise statistics estimator is proposed. The method introduces an improved noise estimation algorithm SageHusa and combines it with UKF, then the algorithm adaptively estimates the noise of the system and the observation in real time, and resists the error caused by inaccurate noise in positioning calculation. Finally, a convergent factor is added to UKF when the algorithm updates the filtering state in order to ensure the convergence of the algorithm. The experiment indicates that the adaptive method increases the precision of pseudo ranges positioning around 40% comparing with the traditional unscented Kalman filter, the method can deal with the influence of inaccurate noise, and the algorithm convergence speed of the algorithm is promoted at the same time, it can be also used in positing system with timevarying noise and unknown statistical noise.