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An Optimal Calibration Method for a MEMS Inertial Measurement Unit
Author(s) -
Bin Fang,
Wusheng Chou,
Ding Li
Publication year - 2014
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.5772/57516
Subject(s) - calibration , scale factor (cosmology) , computer science , inertial measurement unit , kalman filter , observational error , scale (ratio) , allan variance , variance (accounting) , algorithm , control theory (sociology) , artificial intelligence , mathematics , statistics , standard deviation , physics , accounting , control (management) , cosmology , quantum mechanics , metric expansion of space , dark energy , business
An optimal calibration method for a micro-electro-mechanical inertial measurement unit (MIMU) is presented in this paper. The accuracy of the MIMU is highly dependent on calibration to remove the deterministic errors of systematic errors, which also contain random errors. The overlapping Allan variance is applied to characterize the types of random error terms in the measurements. The calibration model includes package misalignment error, sensor-to-sensor misalignment error and bias, and a scale factor is built. The new concept of a calibration method, which includes a calibration scheme and a calibration algorithm, is proposed. The calibration scheme is designed by D-optimal and the calibration algorithm is deduced by a Kalman filter. In addition, the thermal calibration is investigated, as the bias and scale factor varied with temperature. The simulations and real tests verify the effectiveness of the proposed calibration method and show that it is better than the traditional method

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