In order to fully exploit the performance of the MEMS gyroscope and improve the accuracy of the MEMS gyroscope in practical applications,the output signal of the gyroscope array is denoised by constructing a four-gyroscope array combined with the improved SageHusa filtering algorithm. The actual performance of the MEMS gyroscope is effectively improved without changing the gyroscope processing technology and significantly increasing the production cost. By analyzing the systematic error and random error of MEMS gyroscope, the error model is built. The traditional Kalman filter, moving average filter, wavelet threshold denoising and the improved Sage-Husa filtering algorithm are used to denoise the single gyroscope and gyroscope array. Experimental comparison shows that the improved Sage-Husa filtering algorithm combined with the gyroscope array can effectively reduce the output noise of the gyroscope. The random error of the gyroscope array filtered by the improved Sage-Husa algorithm is analyzed by Allan variance. The angle random walk of the four gyroscope array is reduced from 0. 40°/ h to 0. 03°/ h , and the bias instability is reduced from 71. 11°/ h to 5. 83°/ h, which effectively improves the performance of MEMS gyroscope in practical applications.