Joint estimation of system error and state based on cubature Kalman filter

被引：0
作者：
Hu, Zhen-Tao [1 ]
Hu, Yu-Mei [1 ]
Zhang, Jin [1 ]
Yuan, Guang-Yao [1 ]
机构：
[1] Institute of Image Processing and Pattern Recognition, Henan University, Kaifeng
来源：
Guangdianzi Jiguang/Journal of Optoelectronics Laser | 2015年 / 26卷 / 03期
关键词：
Cubature Kalman filter (CKF); Error registration; State estimation; System error;
D O I：
10.16136/j.joel.2015.03.0500
中图分类号：
学科分类号：
摘要：
Aiming at the adverse effects on state estimation precision caused by measurement system error, a novel joint estimation algorithm of system error and state is proposed in this paper. In the new algorithm, combined with the expansion technique of state vector dimension, the error registration model is firstly constructed in the nonlinear filtering framework. Secondly, system error is estimated effectively on the basis of the error registration model, and the adverse effect of system error from measurement residual on filtering precision is improved by the amendment of measurement prediction in cubature Kalman filter. The theoretical analysis and simulation results show the feasibility and effectiveness of the proposed algorithm. ©, 2015, Board of Optronics Lasers. All right reserved.
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页码：535 / 540
页数：5
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