动态磁场校准的九轴惯性融合

Nine-axis inertial fusion method based on dynamic magnetic field calibration

针对低成本MEMS惯性传感器航向角的累积漂移误差和传统磁场校准方法使用不便等问题,提出一种基于动态磁场校准的九轴惯性融合方法。首先,通过旋转矩阵建立陀螺仪与磁力计的关系,利用扩展卡尔曼滤波对陀螺仪数据和磁力计数据进行融合,实现对磁力计的动态实时校准;然后利用互补滤波思想,着重考虑了自由加速度和磁场环境突变的情况,定义了各自的信赖函数,对PI控制器做出了改进;最终获得高稳定性的惯性传感器的姿态角。在传感器采样率为100 Hz,运行时长约为11 min,旋转圈数为117圈时,航向角的漂移为0.42°,与商用的惯导模块算法相比减小了14.9°,实现了数量级的改进。实验结果表明,通过陀螺仪动态校准磁场能有效改善传统椭球拟合算法对校准数据要求高的缺点,提出方法基本可以做到实时,用户无需做特定的绕“8”字动作,即可完成磁场校准;对互补滤波算法进行了改进,基本消除自由加速度对姿态角解算的影响。提出方法在控制减小航向角漂移上有很大优势,同时满足校准便捷、适用场景多样等要求,在低成本MEMS惯导领域有广阔的应用前景。

To address the issue of the accumulated heading angle drift of low-cost MEMS inertial sensors and the inconvenience of using traditional magnetic field calibration methods,a nine-axis inertial fusion algorithm based on dynamic magnetic field calibration was proposed.First,the relationship between the gyroscope and magnetometer was established by a rotation matrix,and the magnetometer was dynamically calibrated by the extended Kalman filter.Second,trust functions were defined considering the free acceleration and the sudden change in the magnetic field environment of the complementary filter,which improved the PI controller.Finally,the attitude angle of the inertial sensor with high stability was obtained.The experimental results show that,the dynamic calibration of the magnetic field by a gyroscope can effectively address the shortcomings of the traditional ellipsoid fitting algorithm,which requires high calibration data.This method can essentially be used in real time,and users can complete magnetic field calibration without a specific“8”winding action.The complementary filtering algorithm is improved to eliminate the influence of free acceleration on attitude angle calculation.When the sampling rate of the sensor is 100 Hz,the running time is approximately 11 min,the number of rotations is 117,and the drift of the heading angle is 0.42°,which is 14.9°less than that of the commercial IMU module,indicating an improvement on the order of a magnitude.This algorithm has considerable advantages in controlling and reducing the heading drift and meets the requirements of convenient calibration and various applicable scenarios.It has a broad application prospects in the field of low-cost MEMS inertial navigation.