R-T-S平滑算法在组合导航后处理中的应用

Sang Tian, Chen Jiabin, Song Chunlei, Yu Huan
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引用次数: 1

摘要

组合导航系统通常采用卡尔曼滤波来实现误差补偿。为了提高导航精度和数据的稳定性,在数据后处理中引入R-T-S (Rauch-Tung-Striebel)最优定间隔平滑。在前向卡尔曼滤波的基础上,加入后向信息滤波,并用实测数据对算法进行验证。结果表明,与传统的卡尔曼滤波相比,R-T-S最优定间隔平滑不仅可以提高位置和姿态的精度,而且可以显著提高失锁情况下的导航精度,使其成为一种有效的数据处理方式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The application of R-T-S smoothing algorithm in the post-processing of the integrated navigation
Integrated navigation system usually uses Kalman filter to make it possible for error compensation. In order to improve the precision of navigation and the stability of data, we introduce the R-T-S (Rauch-Tung-Striebel) optimal fixed-interval smoothing into the post-processing of data. On the basis of the forward Kalman filter, we add the backward information filter to the system and use the measured data 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 posture but can also improve the precision of navigation significantly in case of lock-lose, making it possible as an effective way of data processing.
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