An improved Adaptive Extended Kalman Filter Algorithm of SINS/GPS loosely-coupled integrated navigation system

Yuyan Wang*, Xiuyun Meng, Jilu Liu

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

1 引用 (Scopus)

摘要

The Kalman Filter algorithm usually cannot estimate noise statistics in real-time, in order to deal with this issue, a new kind of improved Adaptive Extended Kalman Filter algorithm is proposed. Based on residual sequence, this algorithm mainly improves the adaptive estimator of the filter algorithm, which can estimate measurement noise in real-time. Furthermore, this new filter algorithm is applied to a SINS/GPS loosely-coupled integrated navigation system, which can automatically adjust the covariance matrix of measurement noise as noise varies in the system. Finally, the original Extended Kalman Filter and the improved Adaptive Extended Kalman Filter are applied respectively to simulate for the SINS/GPS loosely-coupled model. Tests demonstrate that, the improved Adaptive Extended Kalman Filter reduces both position error and velocity error compared with the original Extended Kalman Filter.

源语言英语
页(从-至)87-91
页数5
期刊International Journal of Engineering and Technology(UAE)
7
4
DOI
出版状态已出版 - 2018

指纹

探究 'An improved Adaptive Extended Kalman Filter Algorithm of SINS/GPS loosely-coupled integrated navigation system' 的科研主题。它们共同构成独一无二的指纹。

引用此