Study on Adaptive Filter with MEMS-INS/GPS Integrated Navigation system

被引：0
作者：
Duan, Fengyang [1 ]
Yu, Huadong [1 ]
Li, Xiaolong [2 ]
机构：
[1] Changchun Univ Sci & Technol, Electomech Engn Coll, Changchun, Jilin Province, Peoples R China
[2] Aviat Univ AF, Dept Aviat Control Engn, Changchun, Peoples R China
来源：
2009 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION, VOLS 1-7, CONFERENCE PROCEEDINGS | 2009年
关键词：
integrated navigation Kalman filter adaptive algorithm;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The problem of conventional Kalman filter is that the model uncertainties will severly degrade the system performance. Because of that, the maximum likelihood estimator of innovation-based adaptive Kalman filter is studied in the paper. The improved algorithm is proposed in order to solve the limitation of ML adaptive estimator in the MEMS-INS/GPS integrated navigation system. The simulation results show that the improved algorithm is feasible and efficient.
引用
收藏
页码：401 / +
页数：3
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