基于卡尔曼滤波的MUH姿态信号融合算法研究

利用MEMS陀螺仪和加速度计获取姿态的方法已被广泛用于低成本的民用无人直升机上,陀螺仪的漂移和加速度计中的运动加速度都会影响估计精度,设计了基于四元数的卡尔曼滤波器,根据三轴角速率陀螺和加速度计信号,融合无人直升机姿态信号,并针对陀螺仪的漂移和加速度计的测量误差,设计了自适应的量测噪声方差矩阵,补偿融合精度,得到稳定可靠且精度较高的姿态信息,用于无人直升机的内环增稳控制.实验表明,该方法估值精度较高,能有效解决小型无人直升机姿态求解问题.

The research on attitude determination algorithm based on kalman filter for unmanned helicopter

Inertial measurement method is widely used in attitude determination of low cost civil MUH(Mini Unmanned Helicopter).But the dirft of gyroscope and the kinematic acceleration affect the accuracy of estimation.This paper designed a Kalman filter based on quaternion.According to the gyroscope and accelerometer signal,fusion the attitude of MUH.And designed adaptive covariance matrix of measurement noise to improve the fusion accuracy.Get stable and high accuracy attitude information for stability augmentation system. Experiment data shows that the method can effectively solve the problem of attitude determination of MUH.