基于互补-粒子滤波的MEMS传感组件姿态数据融合算法

Attitude Data Fusion Algorithm for MEMS Sensor Component Based on Complementary-particle Filter

为解决现有的MEMS传感组件精度低、误差大和磁传感器测量的航向角数据噪声大、精度低等问题,提出基于互补-粒子滤波的姿态融合解算方法。先用互补滤波算法结合加速计和磁力计对陀螺仪的姿态角进行修正,再采用四元素法对陀螺仪数据进行粒子滤波。仿真实验结果证明:该算法能快速解算出姿态角,提高解算精度。

In order to solve the problems of low precision and large error of MEMS sensor components and high noise and low accuracy of heading angle data measured by magnetic sensor,a method of attitude fusion based on complementary particle filter is proposed.Firstly,the attitude angle of gyroscope is corrected by using complementary filtering algorithm combined with accelerometer and magnetometer,and then particle filtering is performed on gyroscope data by using four element methods.The simulation results show that the algorithm can quickly calculate the attitude angle and improve the calculation accuracy.