自适应快速弱敏无迹Kalman滤波算法
作者:
作者单位:

1.郑州轻工业大学;2.北京理工大学

作者简介:

通讯作者:

中图分类号:

TL361

基金项目:

国家自然科学基金项目(面上项目,重点项目,重大项目)


Adaptive Fast Desensitized Unscented Kalman Filter Algorithm
Author:
Affiliation:

1.Zhengzhou University of Light Industry;2.Beijing Institute of Technology

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:

    针对弱敏无迹Kalman滤波需要代数求解增益矩阵耗时长和实时选取敏感性权重的问题,通过重新定义敏感性和代价函数获得解析形式的增益矩阵来减少计算时间,并利用量测残差正交原理设计了敏感性权重的自适应因子,提出了自适应快速弱敏无迹Kalman滤波算法,减少计算时间的同时实现了滤波过程中敏感性权重的实时调节。典型算例的数值仿真结果验证了其有效性。

    Abstract:

    Aiming at the problem of desensitized unscented Kalman filtering that large computation time algebraic solution of gain matrix and real-time selection of sensitivity weights, an analytical gain matrix is obtained by redefining the sensitivity and cost functions to reduce computation time, and the adaptive factor of sensitivity weight is designed by principle of measurement residuals. An adaptive fast desensitized unscented Kalman filtering algorithm is proposed, which reduces the calculation time and realizes the real-time adjustment of the sensitivity weight in the filtering process. Numerical simulation results of a typical example verify its effectiveness.

    参考文献
    相似文献
    引证文献
引用本文
分享
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:2020-08-06
  • 最后修改日期:2020-11-23
  • 录用日期:2020-12-03
  • 在线发布日期: 2021-01-04
  • 出版日期: