TY - JOUR
T1 - A MEMS gyroscope high-order calibration method for highly dynamic environments
AU - Wang, Jinwen
AU - Deng, Zhihong
AU - Liang, Xinyu
AU - Liu, Ning
N1 - Publisher Copyright:
© 2020 IOP Publishing Ltd.
PY - 2020/3
Y1 - 2020/3
N2 - In a highly dynamic environment, a Micro Electro Mechanical Systems (MEMS) gyroscope becomes inaccurate after being calibrated using the traditional calibration methods. In this paper, a high-order calibration method for MEMS gyroscopes is proposed. The effects of a highly dynamic environment on gyroscope outputs are analyzed, and a high-order calibration model of the gyroscope is established according to a nonlinear relationship between the measured value and the real value of the gyroscope. An improved generalized recursive least squares (IGRLSs) algorithm is developed to solve the high-order calibration model, and an adaptive forgetting factor is introduced to correct the algorithm update capability. Compared with traditional gyroscope calibration methods, the proposed method solves the problem of data saturation and colored noise, and provides an unbiased and consistent parameter estimation. The results of calibration experiments show that the gyroscope calibration precision of the x-axis (roll axis) and the z-axis (yaw axis) are effectively increased by more than 58.30% and 19.14%, respectively.
AB - In a highly dynamic environment, a Micro Electro Mechanical Systems (MEMS) gyroscope becomes inaccurate after being calibrated using the traditional calibration methods. In this paper, a high-order calibration method for MEMS gyroscopes is proposed. The effects of a highly dynamic environment on gyroscope outputs are analyzed, and a high-order calibration model of the gyroscope is established according to a nonlinear relationship between the measured value and the real value of the gyroscope. An improved generalized recursive least squares (IGRLSs) algorithm is developed to solve the high-order calibration model, and an adaptive forgetting factor is introduced to correct the algorithm update capability. Compared with traditional gyroscope calibration methods, the proposed method solves the problem of data saturation and colored noise, and provides an unbiased and consistent parameter estimation. The results of calibration experiments show that the gyroscope calibration precision of the x-axis (roll axis) and the z-axis (yaw axis) are effectively increased by more than 58.30% and 19.14%, respectively.
KW - IGRLS algorithm
KW - adaptive forgetting factor
KW - high dynamic environment
KW - high-order calibration model of gyroscope
UR - http://www.scopus.com/inward/record.url?scp=85098292284&partnerID=8YFLogxK
U2 - 10.1088/1361-6501/abca55
DO - 10.1088/1361-6501/abca55
M3 - Article
AN - SCOPUS:85098292284
SN - 0957-0233
VL - 32
JO - Measurement Science and Technology
JF - Measurement Science and Technology
IS - 3
M1 - 035115
ER -