Indirect Kalman Filtering Based Attitude Estimation for Low-Cost Attitude and Heading Reference Systems

In this paper, a computational efficient attitude estimation method is proposed for the low-cost attitude and heading reference systems. In the proposed method, the velocity and position provided by the Global Positioning System and inertial sensors outputs are first used to construct the vector obs...

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Bibliographic Details
Published inIEEE/ASME transactions on mechatronics Vol. 22; no. 4; pp. 1850 - 1858
Main Authors Chang, Lubin, Zha, Feng, Qin, Fangjun
Format Journal Article
LanguageEnglish
Published IEEE 01.08.2017
Subjects
Attitude and heading reference systems (AHRS)
attitude estimation
Computational modeling
Estimation
Global Positioning System
global positioning system (GPS)
indirect Kalman filter
Kalman filters
Mathematical model
strapdown inertial navigation system (SINS)
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Summary:In this paper, a computational efficient attitude estimation method is proposed for the low-cost attitude and heading reference systems. In the proposed method, the velocity and position provided by the Global Positioning System and inertial sensors outputs are first used to construct the vector observations. With the constructed vector observations, an error equations based filtering model is established using the Euler angles as the attitude parameterization. If the attitude has been well initialized, the established model can reduce to a linear state-space model, which enables the application of standard Kalman filtering. For the established attitude estimation model, an indirect Kalman filter is detailedly designed. Car-mounted filed test results demonstrate that the proposed method possesses superiority over the existing methods with consideration of both accuracy and efficiency.
ISSN:1083-4435
1941-014X
DOI:10.1109/TMECH.2017.2698639