A Pedestrian Navigation System by Low-cost Dual Foot-Mounted IMUs and Inter-foot Ranging

M. Zhu, Y. Wu, S. Luo
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引用次数: 3

Abstract

Foot-mounted inertial sensors become popular in many indoor or GPS-denied applications, including but not limited to medical monitoring, gait analysis, soldier and first responder positioning. However, the foot-mounted inertial navigation relies largely on the aid of Zero Velocity Update (ZUPT) and has encountered inherent problems such as heading drift. This paper implements a pedestrian navigation system based on dual foot-mounted low-cost inertial measurement units (IMU) and inter-foot ultrasonic ranging. The global observability analysis of the system is performed to investigate the roles of the foot-to-foot ranging measurement in improving the state estimability. A Kalman-based estimation algorithm is mechanized in the Earth frame, rather than in the common local-level frame, which is found to be effective in depressing the linearization error in Kalman filtering. An ellipsoid constraint in the Earth frame is also proposed to further restrict the height drift. Simulation and real field experiments show that the proposed method has better robustness and positioning accuracy (about 0.1–0.2% travelled distance) than the traditional pedestrian navigation schemes do.
基于低成本双足置imu和足间测距的行人导航系统
足部惯性传感器在许多室内或gps拒绝应用中变得流行,包括但不限于医疗监测,步态分析,士兵和第一响应者定位。然而,足部惯性导航在很大程度上依赖于零速度更新(ZUPT),并且遇到了航向漂移等固有问题。本文实现了一种基于双足置低成本惯性测量单元(IMU)和足间超声测距的行人导航系统。对系统进行了全局可观测性分析,探讨了足距测量在提高系统状态可估计性方面的作用。本文提出了一种基于卡尔曼的估计算法,它可以有效地抑制卡尔曼滤波中的线性化误差。为了进一步限制高度漂移,还提出了地球框架中的椭球约束。仿真和现场实验结果表明,与传统行人导航方案相比,该方法具有更好的鲁棒性和定位精度(行走距离约为0.1-0.2%)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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