Abstract: In the ground vehicle integrated navigation, GNSS observations are often interfered by complex ground environment and thus, its positioning result is more prone to contain outliers which can seriously affect GNSS/SINS integrated filter solution. This paper, from the perspective of IMU system error feature, studies an outlier detection method of GNSS/SINS integrated navigation based on accelerometer bias stability. According to the outlier of accelerometer bias result, the method detects gross errors in GNSS position, velocity, etc; and then applies the robust strategies of rejection and weight reduction to resist the influence of gross errors. The method is analyzed by a set of vehicle measured data. The results show that the observation outliers can greatly affect the accelerometer bias result and thus taking the accelerometer bias stability as a condition, the outliers can be exactly detected. In every direction of ENU, the RMS of position and the RMS of velocity are improved by 70.8% and 87.9% respectively; the RMS of attitude is improved by 77.7%. The method greatly improves the accuracy and robustness of integrated navigation results and provides a new strategy for robust processing of integrated navigation data.