Application of extended Kalman filtering algorithm in multi-sensor information fusion

Author

Xu Yejun

Author_Institution

Suzhou Ind. Park Inst. Of Services Outsourcing, Suzhou, China

fYear

2014

fDate

22-24 Aug. 2014

Firstpage

687

Lastpage

691

Abstract

A novel precise Kalman Filter model applied to the attitude control system was presented. Considering not only the non-liner relationship between the measured value of accelerator sensor and Euler Angle but also the conversion of body axis system to geodetic coordinate system. The noise parameter was obtained accurately by using offline testing. The test platform was set up utilizing STM32,and the data of static testing and dynamic testing was provided.

Keywords

Kalman filters; acceleration measurement; aerospace computing; aerospace testing; attitude control; nonlinear filters; sensor fusion; Euler angle; STM32; accelerator sensor; attitude control system; body axis system conversion; dynamic testing; extended Kalman filtering algorithm; geodetic coordinate system; multisensor information fusion; noise parameter; nonliner relationship; offline testing; static testing; test platform; Computers; Equations; Estimation; Gyroscopes; Extended Kalman Filter; attitude control; information fusion; offline testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science & Education (ICCSE), 2014 9th International Conference on

Conference_Location

Vancouver, BC

Print_ISBN

978-1-4799-2949-8

Type

conf

DOI

10.1109/ICCSE.2014.6926549

Filename

6926549