Position tracking of pedestrians by means of inertial sensors is a highly explored field of research. In fact, there are already many approaches to implement inertial navigation systems (INSs). However, most of them use a single inertial measurement unit (IMU) attached to the pedestrian’s body. Since wearable-devices will be given items in the future, this work explores the implementation of an INS using two wearable-based IMUs. A loosely coupled approach is proposed to combine the outputs of wearable-based INSs. The latter are based on a pocket-mounted IMU and a foot-mounted IMU. The loosely coupled fusion combines the output of the two INSs not only when these outputs are least erroneous, but also automatically favoring the best output. This approach is named smart update. The main challenge is determining the quality of the heading estimation of each INS, which changes every time. In order to address this, a novel concept to determine the quality of the heading estimation is presented. This concept is subject to a patent application. The results show that the position error rate of the loosely coupled fusion is 10 cm/s better than either the foot INS’s or pocket INS’s error rate in 95% of the cases.
展开▼
机译：借助惯性传感器对行人进行位置跟踪是一个高度探索的研究领域。实际上，已经有许多实现惯性导航系统（INS）的方法。但是，大多数人使用的是附着在行人身体上的单个惯性测量单元（IMU）。由于将来会为可穿戴设备提供物品，因此这项工作探索了使用两个基于可穿戴设备的IMU实施INS的方法。提出了一种松散耦合的方法来组合可穿戴式INS的输出。后者基于口袋式IMU和脚式IMU。松耦合融合将两个INS的输出合并在一起，不仅在这些输出的错误最少时，而且会自动偏向最佳输出。这种方法称为智能更新。主要挑战是确定每个INS航向估计的质量，该质量每次都会变化。为了解决这个问题，提出了确定航向估计质量的新颖概念。该概念受专利申请的约束。结果表明，在95％的情况下，松耦合融合的位置错误率比脚部INS或袖珍INS的错误率高10 cm / s。
展开▼
