广义系统多传感器分布式融合降阶Kalman滤波器
DOI:
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

O211.64

基金项目:

国家自然科学基金(60374026)和黑龙江大学自动控制重点实验室基金资助


Multisensor Distributed Fusion Reduced Order Kalman Filter for Descriptor Systems
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:

    对于带多传感器的广义线性离散随机系统,应用奇异值分解,将其变换为等价的两个降阶多传感器子系统,提出了基于变换后的状态融合器构造原始状态融合器的新的融合方法。应用Kalman滤波方法,在线性最小方差按矩阵加权、按对角阵加权和按标量加权融合准则下,分别提出了三种最优加权融合降阶广义Kalman滤波器。可统一处理融合滤波、平滑和预报问题。可减少计算负担和改善局部滤波精度。证明了三种融合器和局部估值器之间的精度关系。为了计算最优加权。提出了局部滤波误差协方差阵的计算公式。一个Monte Carlo仿真例子说明了其有效性。

    Abstract:

    For the linear discrete stochastic descriptor systems with multisensor, using me smgu, ar value decomposition, it is transformed into two reduced order subsystems, and a new fusion method of constructing the original state fuser based on the transformed state fuser is presented. Using Kalman filtering method, under the linear minimum variance optimal weighted criterion by matrices, diagonal matrices, and scalars, three optimal weighted fusion reduced order descriptor Kalman estimators are presented respectively. They can handle the fused filtering, smoothing, and prediction problems in a unified framework. They can reduce the computational burden, and can improve the local filtering accuracy. The accuracy relations among three fusers and local estimators are proved. In order to compute the optimal weights, the formula of computing the covariance matrices among local filtering errors is presented. A Monte Carlo simulation example shows its effectiveness.

    参考文献
    相似文献
    引证文献
引用本文

陶贵丽 邓自立. 广义系统多传感器分布式融合降阶Kalman滤波器[J]. 科学技术与工程, 2006, (6): 661-668.
TAO Guili, DENG Zili. Multisensor Distributed Fusion Reduced Order Kalman Filter for Descriptor Systems[J]. Science Technology and Engineering,2006,(6):661-668.

复制
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:2005-12-05
  • 最后修改日期:2005-12-05
  • 录用日期:
  • 在线发布日期:
  • 出版日期:
×
律回春渐,新元肇启|《科学技术与工程》编辑部恭祝新岁!
亟待确认版面费归属稿件,敬请作者关注