基于非线性互补滤波算法的四旋翼飞行器姿态信息融合处理

Data fusion of attitude information of quadrotor based on nonlinear complementary filtering algorithm

针对四旋翼飞行器的MEMS惯性测量单元在姿态测量过程中存在着漂移和噪声误差等问题,在经典互补滤波融合算法的基础上提出了一种改进型的姿态融合处理算法,并搭建了以MPU6050为姿态测量单元的四旋翼飞行器硬件测试平台,分别在静态和动态环境下对惯性测量单元直接解算得到的姿态数据、传统互补滤波融合得到的姿态数据及改进后滤波算法融合得到的姿态信息进行对比。结果表明,改进后的姿态融合算法在静态环境和动态环境下都表现出了优于传统互补滤波的姿态融合处理效果。

Aiming at the problems of drift and noise error generated in attitude measuring process of MEMS inertial measuring unit on quadrotor, an improved attitude fusion algorithm is proposed based on the traditional complementary filtering, and the hardware test platform of quadrotor based on MPU6050 as attitude measuring unit is established. Both in the static and dynamic environments, the attitude data obtained from different methods are compared, such as direct measurement and operation of the inertial measuring unit, data fusion with traditional complementary filtering and the improved filtering fusion algorithm. The results show that the improved attitude fusion algorithm has better effect than traditional complementary filter in both static and dynamic environments.