A Robust Orientation Estimation Algorithm Using MARG Sensors

This paper presents a robust orientation estimation algorithm by using magnetic, angular rate, and gravity sensors. The robustness is achieved by two online methods: compensation of hard iron effect for the magnetometer and separation of the accelerometer signals into gravity projections and linear...

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Vydané v:IEEE transactions on instrumentation and measurement Ročník 64; číslo 3; s. 815 - 822
Hlavní autori: Hu, Jwu-Sheng, Sun, Kuan-Chun
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.03.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
9-D inertial measurement unit (IMU)
Acceleration
and gravity (MARG) sensors
angular rate
direct cosine matrix (DCM)
Estimation
Gravity
gravity projection
Iron
magnetic
Magnetic separation
Magnetometers
orientation estimation
real-time hard iron compensation
sensor fusion
state-constrained Kalman filter
Vectors
and gravity (MARG) sensors
orientation estimation
9-D inertial measurement unit (IMU)
state-constrained Kalman filter
gravity projection
magnetic
sensor fusion
real-time hard iron compensation
angular rate
direct cosine matrix (DCM)
ISSN:0018-9456, 1557-9662
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Popis
Shrnutí:This paper presents a robust orientation estimation algorithm by using magnetic, angular rate, and gravity sensors. The robustness is achieved by two online methods: compensation of hard iron effect for the magnetometer and separation of the accelerometer signals into gravity projections and linear accelerations. Further, direct cosine matrix is used for the rotation matrix relative to the north, east, down frame. The fusion equations are solved using state-constrained Kalman filter. The simulation and experiment results show the effectiveness of the proposed algorithm in estimating the orientation under acceleration and hard iron influence.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0018-9456
1557-9662
DOI:10.1109/TIM.2014.2359815