TY - JOUR
T1 - Temperature compensation method for low cost three-axis MEMS digital angular rate gyroscopes
AU - Tu, Hai Feng
AU - Liu, Li
N1 - Publisher Copyright:
© 2016 Beijing Institute of Technology.
PY - 2016/3/1
Y1 - 2016/3/1
N2 - In recent years, a large number of small volume, low cost micro electro mechanical systems (MEMS) digital three-axis angular rate gyroscopes have been developed and widely used in civil and military fields. However, these kinds of gyroscopes have poor performances in initial zero-bias, temperature drift, In-Run bias stability, bias repeatability, etc., their output errors need to be compensated before being used. Based on a lot of experiments, the temperature drift and the initial zero-bias are the major error sources in the MEMS gyroscopes output data. Due to the poor repeatability of temperature drift, the temperature compensation coefficients need to be recalculated every time before using. In order to recalculate parameters of the temperature compensation model quickly, a 1st-order polynomial model of temperature is established, then a forgetting factor recursive least squares estimator will be adopted to identify the model parameters in real time. Static and dynamic experimental data shows that this method removed/compensated the temperature drift and initial zero-bias from the output of the gyroscopes effectively.
AB - In recent years, a large number of small volume, low cost micro electro mechanical systems (MEMS) digital three-axis angular rate gyroscopes have been developed and widely used in civil and military fields. However, these kinds of gyroscopes have poor performances in initial zero-bias, temperature drift, In-Run bias stability, bias repeatability, etc., their output errors need to be compensated before being used. Based on a lot of experiments, the temperature drift and the initial zero-bias are the major error sources in the MEMS gyroscopes output data. Due to the poor repeatability of temperature drift, the temperature compensation coefficients need to be recalculated every time before using. In order to recalculate parameters of the temperature compensation model quickly, a 1st-order polynomial model of temperature is established, then a forgetting factor recursive least squares estimator will be adopted to identify the model parameters in real time. Static and dynamic experimental data shows that this method removed/compensated the temperature drift and initial zero-bias from the output of the gyroscopes effectively.
KW - Angular rate gyroscope
KW - Least squares
KW - MEMS sensors
KW - Temperature compensation
UR - http://www.scopus.com/inward/record.url?scp=84969233486&partnerID=8YFLogxK
U2 - 10.15918/j.jbit1004-0579.201625.0105
DO - 10.15918/j.jbit1004-0579.201625.0105
M3 - Article
AN - SCOPUS:84969233486
SN - 1004-0579
VL - 25
SP - 28
EP - 34
JO - Journal of Beijing Institute of Technology (English Edition)
JF - Journal of Beijing Institute of Technology (English Edition)
IS - 1
ER -