| 两传感器按对角阵加权信息融合稳态Kalman滤波器 |
| |
| 引用本文： | 高媛,毛琳,梁佐江,邓自立. 两传感器按对角阵加权信息融合稳态Kalman滤波器[J]. 黑龙江大学自然科学学报, 2004, 21(2): 52-54 |
| |
| 作者姓名： | 高媛 毛琳 梁佐江 邓自立 |
| |
| 作者单位： | 黑龙江大学,电子工程学院,黑龙江,哈尔滨,150080 |
| |
| 基金项目： | 国家自然科学基金资助项目(60374026) |
| |
| 摘 要： | 应用现代时间序列分析方法,在按对角阵加权线性最小方差最优信息融合准则下,基于Riccati方程,提出两传感器信息融合稳态最优Kalman滤波器.与按矩阵加权最优融合.Kalman滤波器相比,可减少计算负担,与单传感器情形相比,提高了滤波精度.一个仿真例子说明其有效性.
|
| 关 键 词： | 按对角阵加权最优信息融合准则 信息融合稳态Kalman滤波器 Riccati方程 |
| 文章编号： | 1001-7011(2004)02-0052-03 |
| 修稿时间： | 2003-10-23 |
Two-sensor information fusion steady-state Kalman filter weighted by diagonal matrices |
| |
| GAO Yuan,MAO Lin,LIANG Zuo-Jiang,DENG Zi-li. Two-sensor information fusion steady-state Kalman filter weighted by diagonal matrices[J]. Journal of Natural Science of Heilongjiang University, 2004, 21(2): 52-54 |
| |
| Authors: | GAO Yuan MAO Lin LIANG Zuo-Jiang DENG Zi-li |
| |
| Abstract: | By the modern time series analysis method, under the linear minimum variance optimal information fusion criterion weighted by diagonal matrices, based on the Riccati equation, the two-sensor information fusion steady-state optimal Kalman filter is presented. Compared with optimal fusion Kalman filter weighted by matrices, the computational burden may be reduced. Compared with the single sensor case, the filtering accuracy is improved. A simulation example shows its effectiveness. |
| |
| Keywords: | optimal information fusion criterion weighted by diagonal matrices information fusion steady-state Kalman filter Riccati equation |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
|
