基于足部安装的微机电系统（MEMS）传感器的新型步长估计器。

A Novel Step Length Estimator Based on Foot-Mounted MEMS Sensors.

机构信息

School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China.

出版信息

Sensors (Basel). 2018 Dec 15;18(12):4447. doi: 10.3390/s18124447.

DOI:10.3390/s18124447

PMID:30558332

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6308666/

Abstract

Pedestrian Dead Reckoning (PDR)-based pedestrian navigation technology is an important part of indoor and outdoor seamless positioning services. To improve the performance of PDR, we have conducted research on a step length estimator. Firstly, based on the basic theory of inertial navigation, we analyze in detail the errors in traditional Strapdown Inertial Navigation Systems (SINSs) caused by the unique motion state of pedestrians. Then, according to the fact that the inertial data from the foot can directly reflect the gait characteristics, we conduct a step length estimator that does not rely on SINS. The experimental results show that accuracy of the proposed method is between 0.6% and 1.4% with a standard deviation of 0.25%.

摘要

基于行人航位推算（PDR）的行人导航技术是室内外无缝定位服务的重要组成部分。为了提高 PDR 的性能，我们对步长估计算法进行了研究。首先，基于惯性导航的基本原理，详细分析了传统捷联惯性导航系统（SINS）中由于行人独特的运动状态而产生的误差。然后，根据脚部的惯性数据可以直接反映步态特征的事实，我们提出了一种不依赖 SINS 的步长估计算法。实验结果表明，所提出方法的精度在 0.6%到 1.4%之间，标准差为 0.25%。