基于Allan方差自适应算法的姿态解算

为解决MEMS 姿态传感器的复杂噪声问题，设计使用一种基于Allan 方差的自适应算法在线估计量测噪 声方差。基于Allan 方差递推公式组成自适应算法来追踪数据的方差值，采用欧拉角微分方程作为滤波的状态方程， 通过对陀螺仪静态数据Allan 方差分析得到陀螺仪的主要噪声参数用作滤波系统噪声方差，并将各个数据整合解算 出姿态角。结果表明：自适应滤波算法比常规滤波方法解算的角度精度高，在噪声波动的环境条件下，自适应滤波 算法实用性更好。

Attitude Calculation Based on Allan Variance Adaptive Algorithm

In order to solve the problem of complex noise in MEMS attitude sensor, an adaptive algorithm based on Allan variance is designed to estimate the variance of measured noise on-line. The adaptive algorithm based on Allan variance recurrence formula is utilized to track the variance of on-line data. Eulerian angle differential equations are used as the filtering state equations. The main noise parameters of the gyroscope got by Allan variance analysis of gyro static data are regarded as the noise variance of the filtering system, each data is integrated to figure out the attitude angle. Results show that the algorithm can improve angle discrimination accuracy higher than the conventional filtering method, and under the environment of noise fluctuation, the adaptive filtering algorithm is more practical.