基于MEMS-MARG传感器的消防员室内定位算法

Indoor positioning algorithm for firefighters based on MEMS-MARG sensor

针对消防员在室内环境中进行灭火和救援时难以获知自身位置坐标的问题,采用MEMS-MARG传感器设计了一种室内定位算法。首先,根据加速度幅值波形使用峰值探测法和零点交叉法相结合的方式进行步数检测。然后,通过对消防员的行走路线进行分类,设计了一种基于直线判断辅助的航向反馈修正算法来提高定位精度,并将扩展卡尔曼滤波器融入到行人航迹推算算法中,用于估计消防员的位置坐标。最后,分别按照矩形、三角形、半圆形轨迹,进行了3组实验。实验结果表明,与未使用航向修正算法相比,位置误差减小了45%以上,航向角和位置的均方根误差分别减小了65%和76%以上。所提出的消防员室内定位算法具有良好的定位性能。

In order to solve the problem that it is difficult for firefighters to know their own position coordinates when performing fire extinguishing and rescuing in indoor environment,an indoor positioning algorithm is designed by using MEMS-MARG sensor.First,according to the acceleration amplitude waveform,the step number detection is carried out by the combination of peak detection method and zero crossing method.Then,a heading feedback correction algorithm based on by straight-line judgment assistance is designed to improve the positioning accuracy by classifying the firefighter’s walking routes,and an extended Kalman filter is fused into the pedestrian dead reckoning algorithm to estimate the position coordinates of the firefighters.Finally,three sets of experiments are carried out according to the rectangle,triangle and semicircle trajectories.Experimental results show that the position error is decreased by more than 45%,and the root mean squared(RMS)errors of heading angle and position are decreased by 65%and 76%respectively,which show that the proposed indoor positioning algorithm for firefighters has good positioning performance.