DocumentCode
3257647
Title
Calibration of the accelerometer triad of an inertial measurement unit, maximum likelihood estimation and Cramér-Rao bound
Author
Panahandeh, G. ; Skog, I. ; Jansson, M.
Author_Institution
Signal Process. Lab., KTH-R. Inst. of Technol., Stockholm, Sweden
fYear
2010
fDate
15-17 Sept. 2010
Firstpage
1
Lastpage
6
Abstract
In this paper, a simple method to calibrate the accelerometer cluster of an inertial measurement unit (IMU) is proposed. The method does not rely on using a mechanical calibration platform that rotates the IMU into different precisely controlled orientations. Although the IMU is rotated into different orientations, these orientations do not need to be known. Assuming that the IMU is stationary at each orientation, the norm of the input is considered equal to the gravity acceleration. As the orientations of the IMU are unknown, the calibration of the accelerometer cluster is stated as a blind system identification problem where only the norm of the input to the system is known. Under the assumption that the sensor noises have a white Gaussian distribution the system identification problem is solved using the maximum likelihood estimation method. The accuracy of the proposed calibration method is compared with the Cramér-Rao bound for the considered calibration problem.
Keywords
Gaussian distribution; accelerometers; aircraft instrumentation; inertial navigation; maximum likelihood estimation; white noise; Cramer-Rao bound; IMU; accelerometer cluster; accelerometer triad calibration; inertial measurement unit; maximum likelihood estimation; sensor noise; system identification problem; white Gaussian distribution; Accelerometers; Calibration; Gravity; Maximum likelihood estimation; Minimization; Noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Indoor Positioning and Indoor Navigation (IPIN), 2010 International Conference on
Conference_Location
Zurich
Print_ISBN
978-1-4244-5862-2
Electronic_ISBN
978-1-4244-5865-3
Type
conf
DOI
10.1109/IPIN.2010.5646832
Filename
5646832
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