一种基于加表零偏稳定性的GNSS/SINS组合导航异常探测方法

An Outlier Detection Method of GNSS/SINS Integrated Navigation Based on Accelerometer Bias Stability

在地面车载组合导航中,全球导航卫星系统（global navigation satellite system,GNSS）的观测值容易受地面复杂环境的干扰,导致其定位结果出现异常,严重影响GNSS/捷联惯性导航系统（strap-down inertial navigation system,SINS）组合的滤波解算。从惯导系统误差特性的角度,研究了一种基于加表零偏稳定性的组合导航异常探测新方法。该方法从加表零偏解算的异常来发现GNSS位置、速度等观测值中的粗差,并采取剔除和降权的抗差方法抵御粗差影响。通过一组车载数据的分析表明,观测粗差对加表零偏解算的影响十分显著,以此为判别条件能够准确地发现观测粗差。采用该方法后,位置误差、速度误差和姿态误差的均方根分别减小了70.8%、87.9%和77.7%,显著提高了组合导航的解算精度和鲁棒性,为组合导航数据的抗差处理提供了一种新思路。

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.