基于平方根UKF的伪卫星动态跟踪定位算法
CSTR:
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:

国家“十三五”重点研发计划基金资助项目(2016YFB0502100,2016YFB0502102)


Pseudolite dynamic tracking and positioning algorithm based on square root UKF
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    为了解决传统Kalman滤波在处理非线性系统时的局限性,以及扩展Kalman滤波(EKF)在处理强非线性系统时发散性和精度较差的问题,结合动态导航系统中的目标跟踪定位问题,在不敏Kalman滤波(UKF)算法的基础上,提出了一种基于平方根UKF的动态跟踪定位算法,在递推运算过程中采用协方差矩阵的平方根代替传统算法计算过程中的协方差矩阵。MATLAB仿真结果表明,平方根UKF算法的精度比EKF提升了54.7%,比UKF提升了14.8%。所提出的算法解决了Kalman处理非线性系统的局限性以及传统EKF和UKF算法精度不高的问题,为伪卫星系统的高精度定位研究提供了有力支撑。

    Abstract:

    In order to solve the limitation of traditional Kalman filter in dealing with nonlinear system and the problem of divergence and poor accuracy of extended Kalman filter (EKF) in dealing with strong nonlinear system, a dynamic tracking and positioning algorithm based on square root UKF was proposed based on the unscented Kalman filter (UKF) algorithm in combination with the problem of target tracking and positioning in dynamic navigation system. In the process of recursive operation, the square root of covariance matrix was used to replace the covariance matrix in the calculation process of covariance algorithm. The MATLAB simulation results show that the accuracy of the square root UKF algorithm is 54.7% higher than that of the EKF algorithm, and 14.8% higher than that of the UKF algorithm. The proposed algorithm solves the limitation of Kalman processing nonlinear system and the problem of the low accuracy of traditional EKF and UKF algorithms, and provides a strong support for the high-precision positioning of pseudolite system.

    参考文献
    相似文献
    引证文献
引用本文

段晨浩,王 珏,邓志鑫.基于平方根UKF的伪卫星动态跟踪定位算法[J].河北科技大学学报,2020,41(6):493-499

复制
分享
相关视频

文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2020-08-09
  • 最后修改日期:2020-10-16
  • 录用日期:
  • 在线发布日期: 2020-12-02
  • 出版日期:
文章二维码