基于手机惯性传感器的航向估计算法研究

Research on heading estimation algorithm based on mobile phone inertial sensors

室内导航解算过程中,针对使用手机陀螺仪进行航向解算存在累积误差和比例-积分(PI)控制器参数固定导致滤波器的环境适应性不强等问题,提出一种基于陀螺仪、重力计及磁力计的多传感器融合航向估计算法。结合航向解算中陀螺仪不易受环境影响以及重力计和磁力计不存在累积误差的优点,采用重力计与磁力计补偿陀螺仪的漂移误差,进而更新四元数来解算航向角以降低高频噪声,同时与陀螺仪积分解算的航向角进行卡尔曼滤波(KF)实现数据融合,提高了滤波器的抗干扰能力并有效地降低了积分累积误差对航向估计造成的影响。

Aiming at the problems that in the process of indoor navigation calculation,heading calculation using mobile phone gyroscope has accumulated error and the parameters of PI controller are fixed,which make the environment adaptability of the filter is not strong,a multi-sensor fusion heading estimation algorithm based on gyroscope,gravimeter and magnetometer is proposed.Combining with the advantage that the gyroscope is less affected by the environment and the gravimeter and magnetometer have no accumulated error in the heading calculation,gravimeters and magnetometers are used to compensate for the drift error of the gyroscope,and the heading angle is solved by updating the quaternion to reduce high-frequency noise.At the same time,the Kalman filtering(KF)is used to realize the data fusion with the heading angle calculated by the gyroscope integral,which improves the anti-interference ability of the filter and effectively reduces the influence of the integral accumulation error on the heading estimation.