Feasibility analysis of the robust adaptive Kalman filtering model

被引:0
|
作者
Huang Zhang-yu [1 ]
Chen Xi-qiang [1 ]
机构
[1] Hohai Univ, Coll Earth Sci & Engn, Nanjing 210098, Peoples R China
来源
INTERNATIONAL SYMPOSIUM ON LIDAR AND RADAR MAPPING 2011: TECHNOLOGIES AND APPLICATIONS | 2011年 / 8286卷
关键词
Classical Kalman Filter; Robust Adaptive Kalman Filter; Adaptive factor; Feasibility;
D O I
10.1117/12.913955
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Classic Kalman Filter is a dynamic and efficient data processing method, but there are some limitations. Robust estimation theory will be introduced to the Classical Kalman Filter (CKF) method, that is: Robust Adaptive Kalman Filter (RAKF). There is a clear advantage in reducing the observational errors and the state prediction errors context. In this paper, it uses a dam deformation monitoring example to illustrate that the RAKF is more reliable than the CKF in the deformation monitoring data processing effectively, and it is obviously in inhibiting the aspect of the state prediction errors and the observational errors. It is a viable and effective method of estimation method.
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收藏
页数:9
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