一种基于UKF的MEMS/GPS组合导航算法

刘明雍; 郭 勇; 张立川; 高沛林

doi:10.11993/j.issn.1673-1948.2013.05.007

一种基于UKF的MEMS/GPS组合导航算法

doi: 10.11993/j.issn.1673-1948.2013.05.007

1.
西北工业大学航海学院, 陕西西安, 710072
2.
水下信息与控制重点实验室, 陕西西安, 710072

基金项目: 国家自然科学基金(51179156); 国家自然科学基金青年基金项目(51109179); 教育部博士点基金(20106102120057); 西北工业大学基础基金(JC201228)

详细信息

作者简介:
刘明雍(1971- ), 男, 教授, 博士生导师, 主要从事水下航行器导航与控制的研究.

中图分类号: TJ630.33
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出版历程
- 收稿日期: 2012-12-26
- 修回日期: 2013-03-28
- 刊出日期: 2013-10-20

UKF-Based Algorithm for MEMS/GPS Integrated Navigation System

1.
College of Marine Engineering, Northwestern Polytechnical University, Xi′an 710072, China
2.
Science and Tech-nology on Underwater Information and Control Laboratory, Xi′an 710072, China

摘要

摘要: 针对微电子机械(MEMS)/全球定位(GPS)组合导航系统中, 强非线性引起的扩展卡尔曼滤波(EKF)导航精度不高、滤波性能不稳定、收敛速度慢等问题, 研究了MEMS/GPS组合导航系统无迹卡尔曼滤波(UKF)算法, 避免了EKF繁重的求导计算。本文对2种滤波方法进行了仿真比较, 结果表明, 用UKF的组合导航系统的误差收敛速度比EKF快, 精度也比EKF高, UKF算法更适合于MEMS/GPS组合导航。
- 微电子机械/全球定位组合导航系统 /
- 扩展卡尔曼滤波 /
- 无迹卡尔曼滤波
Abstract: To solve the problems of low navigation accuracy, slow convergence rate and unstable filtering accuracy caused by the strong nonlinearity of the extended Kalman filter(EKF) in micro electro mechanical system/global posi-tioning system(MEMS/GPS) integrated navigation system, an unscented Kalman filter(UKF) is proposed for the MEMS/GPS integrated navigation system. The UKF avoids the heavy derivation in EKF. Simulation results show that the two filtering methods: the error convergence rate of UKF integrated navigation system is faster, the accuracy is higher than the EKF. Comparison between the two algorithms shows that MEMS/GPS integrated navigation system with UKF achieves faster error convergence rate, higher navigation accuracy and enhanced navigation performance.

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参考文献(9)

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