基于微气压传感器的室内行人高度估计方法

Pedestrian Indoor Height Estimation Algorithm Based on Micro Pressure Sensors

摘要:

针对当前气压传感器解算高度存在误差随时间累积的问题,提出了一种基于微气压传感器的室内行人高度估计新方法。该方法结合微气压传感器的输出高度值,对多个相邻时间内的高度值进行合理性判断,并结合室内行人运动状态对高度变化进行约束,使得解算的高度符合室内行人运动规律。通过电脑采集MS5611微气压传感器数据进行仿真验证,结果表明:该方法能够有效地对高度误差进行修正,相较于微气压传感器直接解算的高度,该算法解算的高度更贴合实际情况,解算轨迹也更接近真实轨迹,轨迹的平均闭环误差从1.9%D下降至0.07%D。该算法有效地提高了室内行人高度估计的定位精度,在室内行人三维定位领域具有一定的工程应用价值。

Abstract:

A method for estimating the indoor height of pedestrians based on micro pressure sensors was developed to address the issues of errors accumulated over time in the height calculations performed using the current pressure sensors. In this method, based on the output height value of a micro pressure sensor, an algorithm judges the height values of multiple adjacent time points. It constrains the height change based on the indoor pedestrian movement status such that this change conforms to the indoor pedestrian movement law. Simulations were performed using data from a MS6511 micro pressure sensor. Experimental results indicate that the proposed method effectively corrected height errors. As compared with the height errors calculated using micro pressure sensor data, the trajectories calculated with the proposed method were closer to the real ones. The average closed-loop error decreased from 1.9%D to 0.07%D, effectively improving the positioning accuracy of indoor pedestrian height estimation. This method has engineering application value in the field of indoor 3D pedestrian positioning.