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[1] Zhou Benchuan, Cheng Xianghong,. Robust UKF algorithm in SINS initial alignment [J]. Journal of Southeast University (English Edition), 2011, 27 (1): 56-60. [doi:10.3969/j.issn.1003-7985.2011.01.012]
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Robust UKF algorithm in SINS initial alignment()
鲁棒UKF滤波算法在SINS初始对准中的应用
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
27
Issue:
2011 1
Page:
56-60
Research Field:
Instrument Science and Technology
Publishing date:
2011-03-30

Info

Title:
Robust UKF algorithm in SINS initial alignment
鲁棒UKF滤波算法在SINS初始对准中的应用
Author(s):
Zhou Benchuan Cheng Xianghong
Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology of Ministry of Education, Southeast University, Nanjing 210096, China
周本川 程向红
东南大学微惯性仪表与先进导航技术教育部重点实验室, 南京 210096
Keywords:
unscented Kalman filter(UKF) robustness Krein space initial alignment large heading misalignment angle
无迹卡尔曼滤波 鲁棒性 Krein空间 初始对准 大方位失准角
PACS:
U666.1
DOI:
10.3969/j.issn.1003-7985.2011.01.012
Abstract:
In the traditional unscented Kalman filter(UKF), accuracy and robustness decline when uncertain disturbances exist in the practical system. To deal with the problem, a robust UKF algorithm based on an H-infinity norm is proposed. In Krein space, a robust element is added in the simplified UKF so as to improve the algorithm. The filtering gain is adjusted by the robust element and in this way the performance of the robustness of the filtering algorithm is promoted. In the initial alignment process of the large heading misalignment angle of the strapdown inertial navigation system(SINS), comparative studies are conducted on the robust UKF and the simplified UKF. The simulation results illustrate that compared with the simplified UKF, the robust UKF is more accurate, and the estimation error of heading misalignment decreases from 16.9′ to 4.3′. In short, the robust UKF can reduce the sensitivity to the system disturbances resulting in better performance.
针对系统存在不确定性扰动时传统UKF滤波算法的滤波精度和鲁棒性均下降的问题, 提出了一种基于H范数的鲁棒UKF滤波算法.该算法在Krein空间内对简化UKF滤波算法进行改进, 增加了一个鲁棒环节.鲁棒环节通过引入给定正常数调整滤波增益从而提高滤波算法的鲁棒性能.在SINS大方位失准角初始对准中对简化UKF滤波算法和鲁棒UKF滤波算法进行了对比研究.仿真结果表明:与简化UKF滤波算法相比, 鲁棒UKF滤波算法的方位失准角估计误差由16.9′缩小到4.3′.鲁棒UKF滤波算法降低了系统对扰动的敏感度, 具有更好的滤波性能.

References:

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Memo

Memo:
Biographies: Zhou Benchuan(1984—), male, graduate; Cheng Xianghong(corresponding author), female, doctor, professor, xhcheng@seu.edu.cn.
Foundation item: The National Basic Research Program of China(973 Program)(No.613121010202).
Citation: Zhou Benchuan, Cheng Xianghong. Robust UKF algorithm in SINS initial alignment[J].Journal of Southeast University(English Edition), 2011, 27(1):56-60.[doi:10.3969/j.issn.1003-7985.2011.01.012]
Last Update: 2011-03-20