R-T-S平滑算法在捷联惯性异航系统初始对准精度事后评估中的应用

Application of R-T-S Optimal Smoothing Algorithm to the Post-Assessment of SINS Alignment

捷联惯性导航系统(SINS)通常采用Kalman滤波实现初始对准.由于R-T-S最优固定区间平滑算法的精度比Kalman滤波高,采用R-T-S最优平滑算法通过事后处理SINS对准数据来计算SINS的失准角,作为参考失准角,对SINS初始对准的精度进行事后评估.以船用SINS为例进行了仿真.结果表明,R-T-S最优平滑算法的精度比Kalman滤波精度高,从而说明利用R-T-S平滑算法对SINS初始对准精度进行事后评估是可行的.

In strapdown inertial navigation system (SINS), an initial alignment Kalman filter is usually used to evaluate the misalignment angles. The precision of optimal smoother is higher than that of Kalman filter from the theory. This paper presented an application of R-T-S fixed-interval optimal smoothing technique to calculate the misalignment angles by post processing of alignment data, then used it as the reference misalignments to assess SINS alignment precision. The simulation was done with marine SINS and the simulation schematic figure was given. The results show that the precision of R-T-S smoothing algorithm is higher than that of Kalman filter and it can effectively evaluate the performance of SINS alignment.