基于手机陀螺仪航向修正算法

Heading correction algorithm based on mobile phone gyroscope

将低价位手机(魅蓝NOTE3)中的陀螺仪作为研究对象,为了减少由于陀螺仪漂移带来的航向误差,鉴于改进的启发式消除算法(iHDE)在航向修正的优越性,对基于行人导航算法框架IEZ的iHDE算法做出改进。由于人们携带手机的方式不同于脚踏式惯性单元IMU,IEZ算法框架已不再适用,故将iHDE应用在基于步态分析和航向估计的行人航迹推算定位算法框架(SHS-PDR)中,并把航向与主方向的偏差作为唯一的状态量输入到卡尔曼滤波器中,得到航向的最优估计,即简化了原始iHDE算法。最后,设计了两类不同难度的行走实验,即常规路线实验与挑战性路线实验,且实验中定位误差分别为总行进距离的0.2%与0.9%,定位精度与未经航向修正的算法相比分别提升了88.9%与43.8%。实验证明,应用在基于手机传感器的SHS-PDR算法框架下的iHDE算法依然保持其良好的航向修正能力。

This paper takes the gyroscope in the mobile phone（Mei Lan NOTE3） as the research object and aims to reduce the heading error caused by the drift of the gyroscope. According to the superiority of the improved heuristic drift elimination（i HDE） algorithm in course corrections, an improved i HDE algorithm based on the pedestrian navigation algorithm framework IEZ is proposed. Since the IEZ algorithm framework is not applicable due to the fact that the way people carrying the mobile phone is different from that of the foot inertial unit IMU, the i HDE algorithm is applied to the pedestrian dead reckoning estimation algorithm（SHS-PDR） based on the gait analysis and heading estimation. Meanwhile, to obtain the optimal heading estimation, the deviation between the heading and the main direction is inputted into the Kalman filter as the only state parameter, which can simplify the original i HDE algorithm. Finally, two kinds of walking experiments（routine route experiment and challenging route experiment） are designed and carried out, which show that the positioning errors are 0.2% and 0.9% of the total experimental distance respectively, and the positioning accuracies are improved by 88.9% and 43.8% respectively compared with those without heading correction. The experiment results verify that the i HDE algorithm applied in the SHS-PDR algorithm framework based on the mobile sensor still maintains good heading correction capability.