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《Journal of Harbin Engineering University》 2010-09
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Algorithm for a MEMS gyroscope based on Kalman filter

QIAN Hua-ming1,XIA Quan-xi2,QUE Xing-tao1,ZHANG Qiang1(1.College of Automation,Harbin Engineering University,Harbin 150001,China;2.Institute of Surveying and Mapping,Information Engineering University of PLA,Zhengzhou 450002,China)  
In order to improve the performance of gyroscopes,the random drift of a micro-electro-mechanical system(MEMS) gyro was analyzed and modeled.Based on the basic principles of time series analysis,AR(1) was adopted to model the preprocessed data measured by a MEMS gyroscope.An augmenting state vector was used to design the Kalman filter.By simulating a rate test and an oscillating test,it was demonstrated that in the cases of static state or constant angular rate,the mean value and standard deviation of the errors were much smaller after filtering than before filtering.However,the effect decreased when it was in an oscillating state.With an amplitude increase,the mean values and standard deviations of errors also increased.The problem was analysed and two methods were adopted to reduce the effect.These involved increasing the sample rate and adopting an adaptive Kalman filter.The simulation demonstrated that both methods could improve the performance of the filter.However,considering of practical limits to sampling rates as well as the calculation speed of the CPU,an adaptive Kalman filter is more practical.
【CateGory Index】: V241.5
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