一种在线调节的联邦卡尔曼组合导航方法

高沛林

doi:10.11993/j.issn.2096-3920.2017.02.005

一种在线调节的联邦卡尔曼组合导航方法

doi: 10.11993/j.issn.2096-3920.2017.02.005

高沛林

西安科技大学电气与控制工程学院, 陕西西安, 710054

详细信息

作者简介:
高沛林(1988-), 女, 硕士, 主要研究方向为导航与控制系统、电力电子技术.

中图分类号: TJ630.33; TN967.2
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- 文章访问数: 1101
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- 被引次数: 0
出版历程
- 收稿日期: 2016-12-06
- 修回日期: 2017-01-13
- 刊出日期: 2017-06-20

An Online Regulation Method of Federated Kalman Filter for Integrated Navigation

GAO Pei-lin

School of Electrical and Control Engineering, Xi′an University of Science and Technology, Xi′an 710054, China

摘要

摘要: 针对水下航行器导航定位研究中, 系统量测噪声统计特性未知时联邦卡尔曼滤波器不稳定, 甚至发散的特点, 文中提出了一种在线调节的自适应联邦滤波方法。该方法利用子系统理论残差和实际残差的比值, 构造了自适应调整量测噪声方差因子, 对子系统量测噪声进行在线调节, 实现了联邦卡尔曼滤波的自适应估计。将该算法应用到惯性导航/多普勒/地磁(SINS/DVL/GNS)组合导航系统中, 并与标准联邦Kalman滤波进行对比。仿真结果表明, 该算法在噪声统计特性未知的情况下, 收敛性比标准联邦卡尔曼滤波好, 具有较高的滤波精度。
- 水下航行器 /
- 组合导航 /
- 联邦滤波 /
- 自适应
- underwater vehicle /
- integrated navigation /
- federated filter /
- adaptive

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参考文献(12)

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