文章摘要
引用本文:桑田,陈家斌,宋春雷,余欢.R-T-S平滑算法与抗差Kalman在数据后处理中的应用[J].导航定位与授时,2018,5(3):24-29 本文二维码信息
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R-T-S平滑算法与抗差Kalman在数据后处理中的应用
The Application of R-T-S Smoothing Algorithm and Robust Kalman Filtering in the Post-processing of the Integrated Navigation
  
DOI:
中文关键词:  捷联惯导  组合导航  后处理  抗差Kalman  最优平滑算法
English Keywords:SINS  Integrated navigation  Post-processing  Robust Kalman filter  Optimal smoothing algorithm
基金项目:国家自然科学基金(91120010)
作者单位
桑田 北京理工大学 自动化学院北京 100081 
陈家斌 北京理工大学 自动化学院北京 100081 
宋春雷 北京理工大学 自动化学院北京 100081 
余欢 北京理工大学 自动化学院北京 100081 
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中文摘要:
      为了提高组合导航系统后处理精度和数据稳定性,将R-T-S最优固定区间平滑算法引入数据后处理中,在前向Kalman滤波的基础上,进行了后向R-T-S最优固定区间平滑处理,并针对GPS观测值中存在异常的问题,将抗差Kalman滤波算法引入数据后处理中,并对该算法进行实物仿真。结果表明,与传统Kalman滤波相比,R-T-S平滑算法不仅可以提高位置、姿态精度,而且在卫星信号失锁的情况下精度也得到显著改善,并且在不丢星的时刻,抗差Kalman滤波可以有效处理GPS信号中的异常观测值,遏制滤波发散,是一种有效的数据处理方法。
English Summary:
      In order to improve the post-processing accuracy of integrated navigation and the stability of data, the R-T-S (Rauch-Tung-Striebel) optimal fixed-interval smoothing is introduced into the post-processing of data. On the basis of the forward Kalman filter, the backward R-T-S optimal fixed-interval smoothing is added to the system, and the robust Kalman filtering is introduced into the post-processing of data to deal with the outlier in the progress as well. The measured data has been used to verify the algorithm. The results show that, compared with the traditional Kalman filter, the R-T-S optimal fixed-interval smoothing can not only improve the precision of the position and attitude, but can also improve the precision significantly in the case of lock-lose; besides, when GPS signal is available,the robust Kalman filtering can effectively deal with the outlier in the observation of GPS signals and restrain the filtering divergence, making it possible to be an effective way of data processing.
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