A redundant fused MIMU attitude system algorithm based on two-stage data fusion of MEMS gyro clusters array. (November 2021)

• Record Type: Journal Article
• Authors: Xue, Liang; Yang, Bo; Yang, Xiaogang; Yuan, Ding; Wang, Xinguo; Chang, Honglong
• Is Part Of: Measurement. Volume 184(2021)
• Publication Date: 2021-11
• Subjects: MEMS gyroscope -- Sensor array -- Kalman filter -- Data fusion -- Attitude estimation; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2021.109993
• Languages: English
• ISSNs: 0263-2241

Abstract

Graphical abstract: Highlights: A fused MIMU attitude algorithm composed of two-stage data fusion is proposed. Theoretical mathematical model for the data fusion is described. A KF is designed to fuse outputs of gyro arrays to create fused MIMU rate signals. Gauss-Newton algorithm is used to estimate quaternion for KF measurements. ARW and RRW noise of gyro are reduced by a factor of 4.86 and 3.8 by the KF. Abstract: A redundant fused microelectromechanical inertial measurement unit (MIMU) attitude system composed of a two-stage data fusion is proposed. In the first stage, multiple gyroscopes are arranged on the axes of the MIMU, and a KF is presented to fuse measurements of the gyro arrays. In the second stage, an integrated KF is designed to estimate attitude quaternion, in which the Gauss-Newton algorithm is used to estimate quaternion to construct KF measurements. Lastly, a fused MIMU with three eight-gyro arrays is developed. The results show that the ARW and RRW are reduced by a factor of about 4.86 and 3.8 respectively, and the quaternion error solved by the fused signals is smaller than that by the original MIMU signals. Additionally, the 1σ error of quaternion components q 0, q 1 and q 3 are each reduced by half while q 2 is reduced to 13% of the corresponding error using the original MIMU signals.