Sensors | |
Improved Iterative Calibration for Triaxial Accelerometers Based on the Optimal Observation | |
Jie Yang1  Wenqi Wu1  Yuanxin Wu2  | |
[1] College of Mechanical Engineering and Automation, National University of Defense Technology, Changsha 410073, China; | |
关键词: triaxial accelerometers; maximum likelihood estimation; iterative calibration; nonlinear; optimization; | |
DOI : 10.3390/s120608157 | |
来源: mdpi | |
【 摘 要 】
This paper presents an improved iterative nonlinear calibration method in the gravitational field for both low-grade and high-grade triaxial accelerometers. This calibration method assumes the probability density function of a Gaussian distribution for the raw outputs of triaxial accelerometers. A nonlinear criterion function is derived as the maximum likelihood estimation for the calibration parameters and inclination vectors, which is solved by the iterative estimation. First, the calibration parameters, including the scale factors, misalignments, biases and squared coefficients are estimated by the linear least squares method according to the multi-position raw outputs of triaxial accelerometers and the initial inclination vectors. Second, the sequence quadric program method is utilized to solve the nonlinear constrained optimization to update the inclination vectors according to the estimated calibration parameters and raw outputs of the triaxial accelerometers. The initial inclination vectors are supplied by normalizing raw outputs of triaxial accelerometers at different positions without any
【 授权许可】
CC BY
© 2012 by the authors; licensee MDPI, Basel, Switzerland
【 预 览 】
Files | Size | Format | View |
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RO202003190043814ZK.pdf | 595KB | download |