微惯性/卫星组合导航高精度事后基准确定方法

针对高性能MEMS组合导航系统的高精度定位定姿需求,提出了一种基于GNSS(Global Navigation Satellite System)精密相对定位RTK(Real-time Kinematic Positioning)和MIMU(MEMS-based Inertial Measurement Unit)组合的高精度事后基准确定算法,该算法在MIMU/RTK组合导航正向Kalman滤波的基础上,采用RTS(Rauch-Tung-Striebel)反向平滑再次进行信息融合,提升了组合导航结果的事后处理精度。另外,通过Allan方差分析技术实现对MIMU随机误差精细建模和MIMU/RTK组合导航相对精度分析。对实测的车载动态试验数据处理结果的均方根误差和Allan方差分析表明:相对于传统正向滤波方法,RTS反向平滑方法能够将MIMU/RTK组合导航定位、定姿精度分别提升45.2%和54.1%。该方法可作为GNSS/INS组合导航高精度参考基准的确定方法。

Fixed-interval smoothing post-processing algorithm for low-cost MEMS-based integrated navigation system

In order to obtain accurate reference results for low-cost MEMS-based system without highprecision POS (Positioning and Orientation System),a fixed-interval smoothing post-processing algorithm is proposed based on GNSS real-time kinematic positioning and MIMU (MEMS-based Inertial Measurement Unit).In this algorithm,a forward Kalman filter for MIMU/RTK (Real-Time Kinematic positioning) integration is established with inertial sensor residuals modeled by Allan variance technique,and a backward RTS (Rauch-Tung-Striebel) smoother is adopted to optimally estimate the navigation states.Field test results are analyzed by means of RMS (root mean square) and Allan variance to evaluate the absolute and relative accuracy,which indicate that the proposed algorithm can improve the position and attitude estimation accuracies of MIMU/RTK integration by 45.2％ and 54.1％ respectively,compared with the traditional forward filtering method.The proposed post-processing method can be used to determine the high-precision reference of GNSS/INS integrated navigation.