为了实现微纳卫星MEMS陀螺动态在线滤波, 对MEMS陀螺阵列建模, 设计可应用于动态过程的最优在线数据融合算法, 建立陀螺阵列测试系统, 并对融合滤波的陀螺系统的性能对比分析。首先, 建立多个陀螺的量测模型。接着基于信息融合模型, 使用Kalman滤波算法, 对预测的协方差矩阵进无求逆运算迭代; 然后, 基于误差估计, 对动态时变信号滤波模型建模, 并给出了融合滤波方法; 最后, 搭建6个MEMS陀螺在线滤波系统, 验证该算法的有效性。实验结果表明: 滤波误差可降低为单陀螺采样误差的1/15, 精度提高一个数量级; 运算量相比层序式滤波减少为1/4, 计算时间减少为1/3。本文所提算法在提高精度的基础上, 显著提高了MEMS陀螺系统的性能指标, 拓展了MEMS陀螺在微纳卫星的应用范围。

A model was established and an optimal data fusion algorithm was designed to realize the online dynamic data fusion of multi-gyroscopes. The data fusion system performance was compared by building a test system. First, a multi-gyros measurement model was established, then the Kalman method was used to estimate the covariance matrix based on the signal fusion model. There was no matrix inversion during this process. The filtering process, applicable to time varying signals, was utilized. Finally, the effectiveness of the algorithm was verified by an online test system using six MEMS gyros. Experimental results indicate that the signal error is reduced to 1/15. In addition, the accuracy is improved one level and reduced to 1/4, and the computation is reduced to 1/3. A system with this new signal fusion algorithm will show improved accuracy and performance, extending the application range of the micro-nano satellite.