杨元喜. 多源传感器动、静态滤波融合导航[J]. 武汉大学学报 ( 信息科学版), 2003, 28(4): 386-388,396.
引用本文: 杨元喜. 多源传感器动、静态滤波融合导航[J]. 武汉大学学报 ( 信息科学版), 2003, 28(4): 386-388,396.
YANG Yuanxi. Kinematic and Static Filtering for Multi-Sensor Navigation Systems[J]. Geomatics and Information Science of Wuhan University, 2003, 28(4): 386-388,396.
Citation: YANG Yuanxi. Kinematic and Static Filtering for Multi-Sensor Navigation Systems[J]. Geomatics and Information Science of Wuhan University, 2003, 28(4): 386-388,396.

多源传感器动、静态滤波融合导航

Kinematic and Static Filtering for Multi-Sensor Navigation Systems

  • 摘要: 首先给出联邦滤波各局部输出量之间的相关协方差矩阵,进而给出了基于各传感器独立观测信息的动、静态滤波解法,这种解法避免了重复使用载体状态方程信息的问题,保证了多传感器数据融合的最优性,而且很容易扩展到抗差滤波和自适应滤波融合。

     

    Abstract: An efficient signal fusion method is put forward for the integrated navigation of the multiple sensor system.To show the correlations of the master filter and the local filters,the covariance matrix among the local filter outputs and that of the local filter and master filter outputs are presented.In order to avoid the correlations between the fusion data sets of the multiple sensors,a synthetic Kalman filtering composed by a kinematic Kalman filtering step and several static Kalman filtering steps is presented.The new developed robust Kalman filtering and the adaptively robust Kalman filtering can be easily extended in this kind of synthetic filtering.

     

/

返回文章
返回