基于智能手机MARG传感器的行人导航算法

Pedestrian navigation algorithm based on the smart phone MARG sensors

对于手持式移动设备的定位导航需求,特别是在室内无法接收到GPS信号的恶劣环境,提出了一种基于智能手机上的磁力计,陀螺仪和加速度计(magnetic,angular rate and gravity,MARG)传感器的行人导航算法,该算法在行人航迹推算的基础上,利用数字低通滤波器滤波后的加速度计三轴模值数据,对行人步态进行检测,采用经验模型对行人步长进行估计,并结合扩展卡尔曼滤波器,采用自适应的方式实时调整测量噪声协方差矩阵,将MARG传感器融合数据用于最佳航向角估算。在智能手机平台上进行测试验证,实验结果表明,在无磁或有磁干扰环境下,所提出的行人导航算法均可保证准确、可靠、持续的位置信息。

The demand for navigating a user with a hand-held device, especially in GPS denied environments, has tremen-dously increased over the last five years. Based on this, this paper presented pedestrian navigation algorithm based on smart phone magnetic, angular rate and gravity （MARG）sensors, which is on the basis of pedestrian dead reckoning algorithm, u- sing a low-pass filter filtered accelerometer data to detect pedestrian step, using an empirical model to estimate the pedestri- an step length, and we designed an extended Kalman filter, using adaptive way to adjust timely measurement noise eovari-ance matrix, to fuse the MARG sensor data and to estimate the optimal heading angle. Validation tests on the smart phone platform, and experimental results show that the non-magnetic or magnetic interference environment, pedestrian navigation proposed algorithm can ensure accurate, reliable, continuous location information.