Research on Gyroscope Array Based on Kalman Filter

doi:10.3969/j.issn.1000-1093.2016.02.012

Abstract

Abstract: The same type of measurement axes of gyroscope are parallel to each other. The information processing algorithms to improve the accuracy of inertial measurement via gyroscope array are researched. Two different drift models of single MEMS gyroscope are established, and the random drift coefficients are identified via Allan variance. Then the identified random drift coefficients are used for Kalman filter, and the muti-gyroscopes information is fused to acquire a highly precise output of gyroscope array through Kalman filter. The result proves the stability of Kalman filter. Finally, the advantages and disadvantages of different modeling methods are compared by experiment. The experimental results show that the accuracy of MEMS gyroscope can be improved effectively by the information fusion method based on Kalman filter.

Key words: control science and technology, gyroscope array, information fusion, Kalman filter

CLC Number:

TP14

LIU Ming-yong, ZHU Li, DONG Hai-xia. Research on Gyroscope Array Based on Kalman Filter[J]. Acta Armamentarii, 2016, 37(2): 272-278.

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