A novel Kalman filter for combining outputs of MEMS gyroscope array

In this paper, a Kalman filter for combining outputs of a gyroscope array is presented to improve the accuracy of microelectromechanical system (MEMS) gyroscope. A theoretical mathematical model for the accuracy improvement is described. Especially, a discrete-time filter is designed by solving the covariance differential equation with an analytic solution. Performances of presented filter are analyzed by the simulations. Finally, a developed system consisting of six-gyroscope array is implemented to test the performance of the Kalman filter. The experimental results showed a noise density of 0.03°/s/√Hz for the combined rate signal compared to the 0.11°/s/√Hz for the individual gyroscope in the array. The analysis of results measured from Allan variance demonstrated a bias instability of 17.2°/h and angular random walk of 1.6°/√h, whereas the corresponding values for the individual gyroscope is 62°/h and 6.2°/√h, respectively. It proved that the presented approach is effective to improve the MEMS gyroscope accuracy.

► Fusing outputs of the MEMS gyroscopes array to improve accuracy is presented.
► Theoretical mathematical model for the accuracy improvement is described.
► A combined Kalman filter is designed and analyzed by an analytic solution.
► A linear equation is developed for choosing a variance for modeling rate signal.
► ARW and bias drift are reduced from 6.2°√h to 1.6°√h and 62°/h to 17.2°/h by KF.