Noise reduction of MEMS gyroscope based on MUBF algorithm

Due to uncertain bias drift of the micro electro mechanical system (MEMS) gyroscope, the minimum upper-bound filter (MUBF) algorithm is presented to reduce the signal noise of MEMS gyroscope. Here, the bias drift is treated as unknown disturbance. In pursuit of the maximum variance value of the bias drift, the convex optimization process is then utilized to estimate the angular rate output of the MEMS gyroscope. Compared with the Kalman filter (KF) algorithm, the MUBF algorithm can work without a priori delicate bias drift evolvement model, while the condition of the filter existence is easily satisfied. Experimental results show that filtering effectiveness based on the MUBF algorithm is remarkable to suppress the bias drift of the MEMS gyroscope and better than that of the KF algorithm. The proposed method provides a new way to decrease the signal noise of the MEMS gyroscope in practice.