DocumentCode :
581868
Title :
Automatic calibration and in-motion alignment of an odometer-aided INS
Author :
Qingzhe, Wang ; Mengyin, Fu ; Xuan, Xiao ; Zhihong, Deng
Author_Institution :
Sch. of Autom., Beijing Inst. of Technol., Beijing, China
fYear :
2012
fDate :
25-27 July 2012
Firstpage :
2024
Lastpage :
2028
Abstract :
In-motion alignment problem has been regarded as a challenging problem for years in the extensive study on inertial navigation systems (INS´s). In this contribution, the problem of odometer-aided in-motion alignment is investigated, where the nonholonomic constraints are efficiently employed in the designed Kalman filtering process with the measured data provided by a calibrated odometer. As the application of odometer under nonholonomic constraints requires the INS body axes to be well aligned with the vehicle body frame (VBF), INS-to-VBF alignment and calibration of odometer´s scale factor are implemented in the INS/Odometer integration. To the end of in-motion alignment, the system and measurement equations for INS/Odometer integration are derived to construct a Kalman filter, which is used to process the integrated velocity information and then to obtain estimates of both odometer error states and INS error states. With these parameter estimates, the odometer outputs can be calibrated properly, which makes the in-motion alignment implementable and practical. The effectiveness of the proposed method is tested through ground based navigation experiments.
Keywords :
Kalman filters; calibration; distance measurement; inertial navigation; inertial systems; measurement errors; motion measurement; state estimation; INS error state estimation; INS-to-VBF alignment; Kalman filtering process; automatic odometer scale factor calibration; in-motion alignment problem; inertial navigation system; integrated velocity information; measurement equation; nonholonomic constraint; odometer error state estimation; odometer-aided INS; parameter estimation; vehicle body frame; Accuracy; Equations; Kalman filters; Mathematical model; Measurement uncertainty; Navigation; Vehicles; INS-to-VBF Alignment; In-motion Alignment; Inertial Navigation System; Kalman Filter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2012 31st Chinese
Conference_Location :
Hefei
ISSN :
1934-1768
Print_ISBN :
978-1-4673-2581-3
Type :
conf
Filename :
6390257
Link To Document :
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