基于MARG传感器的头部姿态解算方法研究

A Head Pose Algorithm Based on the MARG Sensor

针对头盔显示器(HMD)的头部姿态检测系统中单一传感器进行头部姿态解算准确度低、精度粗略的问题,提出了一种基于MARG传感器的头部姿态解算方法。将互补滤波与PI算法相结合估算陀螺仪的漂移误差,再通过扩展卡尔曼滤波(EKF)实现姿态数据融合。设计了由CC1310、陀螺仪、加速度计和磁强计组成的头部姿态检测单元进行测试实验。与单独的EKF对比,结果表明,这种算法对陀螺仪自身的漂移和加速度计噪声有抑制作用,提高了头部姿态解算的精度和稳定性。

Since the single-sensor based head pose measuring system of the Helmet-Mounted Display(HMD) suffers from low accuracy and poor precision,a novel algorithm based on the information fusion of MARG sensor is proposed.First,the complementary filtering is combined with PI algorithm to estimate the gyroscope drift error,and then the pose data fusion is implemented by using the Extended Kalman Filter(EKF).We made experiments to compare the performance of the conventional single EKF and the proposed algorithm in filtering by using the measuring system composed of a CC1310,a gyroscope,an accelerometer and a magnetometer.The results demonstrate that the proposed algorithm can restrain the drift of the gyroscope and the noise of the accelerometer,and consequently improve the stability and precision of the head pose algorithm.