中文摘要：

提出了一种基于阵列数据融合的虚拟陀螺技术来提高微机械陀螺的精度．其将多个同类型的陀螺组合形成阵列．采用Allan方差方法提取微机械陀螺的速率随机游走、角度随机游走等噪声，并利用阵列陀螺间同类噪声的相关性建立卡尔曼滤波器的系统噪声方差阵及量测噪声方差阵，设计实现了静态和动态两种最优滤波器对陀螺的输出进行最优估计．实验结果显示：三个偏置稳定性为35deg／hr的微陀螺经静态、动态滤波后，所形成的虚拟陀螺偏置稳定性分别降至0．15deg／hr和20deg／hr，表明该虚拟陀螺技术可有效提高微机械陀螺的精度．

英文摘要：

A method based on multi-sensor fusion is proposed to improve the accuracy of micromachined gyroscopes. Several gyroscopes of the same kind form a to extract rate random walk noise and angle random correlation between noises from different gyroscopes gyroscope array. Allan variance estimation is adopted walk noise of each microgyro. Especially, the cross is used in Kalman filter to establish the system noise covariance matrix and the measurement noise covariance matrix. The statistic and dynamical Kalman filters are designed separately to obtain their corresponding optimal estimation of the gyroscope array＇s output. The results of experiments indicate that the three microgyros, each with 35 degree per hour drift, after statistic and dynamical filtering, give a virtual drift of 0.15 degree per hour and 20 degree per hour respectively. This approves that the method of multi-sensors fusion can increase the mircogyro＇s accuracy effectively.