Indoor Relative Positioning Method and Experiment Based on Inertial Measurement Information/Human motion model/UWB Combined System

Yanshun Zhang, Nan Wang, Ming Li, Xue Sun, Zhanqing Wang
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引用次数: 4

Abstract

Navigation and positioning services are related to national security, economic development and social livelihood, they're playing a decisive and indispensable role in both military and civilian fields. Urbanization is accelerating and indoor sites are increasing. People spend more than 80% of their time living and working in the indoor environments (including large buildings, underground sites, mines, tunnels, etc.), How to achieve high-precision navigation and positioning in such a complex navigation environment? This is not only an urgent social problem but also a technical problem. Based on the introduction of indoor navigation background, an inertial measurement information/UWB combined indoor positioning method is proposed in this paper, to solve the problem of long-term positioning in a complex indoor environment, and the experimental researches have been performed. Firstly, based on the research of human motion model, the method extracts motion parameters related to navigation and establishes the mapping model between human motion parameters and navigation parameters in order to implement autonomous pedestrian navigation which is based on inertial measurement information/human motion model. Then, using the position information provided by UWB as the measurement, the Kalman filter based on inertial measurement information/ human motion model/UWB combined system is designed to integrate positioning information from the combined system of inertial measurement information/human motion model and UWB, so that it can provide long-term and high-precision relative navigation for indoor pedestrians. The paper develops a prototype of the inertial measurement information/human motion model/UWB combined system, which provides a physical platform for the experimental verification of the proposed method. What's more, it also optimizes and verifies the proposed method referring to experiments under the environment of NOKOV high-precision indoor 3D-motion capture system by Beijing measurement technology co., LTD. There are bright application prospects that the method can be extended in single-soldier system, urban anti-terrorism operations and pedestrian positioning in the field of emergency rescue.
基于惯性测量信息/人体运动模型/超宽带组合系统的室内相对定位方法与实验
导航定位服务关系到国家安全、经济发展和社会民生,在军事和民用领域都发挥着举足轻重、不可或缺的作用。城市化正在加速,室内场地正在增加。人们80%以上的时间是在室内环境(包括大型建筑、地下场地、矿山、隧道等)中生活和工作的,如何在如此复杂的导航环境中实现高精度的导航定位?这既是一个迫切的社会问题,也是一个技术问题。本文在介绍室内导航背景的基础上,针对复杂室内环境下的长期定位问题,提出了一种惯性测量信息/超宽带组合室内定位方法,并进行了实验研究。该方法首先在研究人体运动模型的基础上,提取与导航相关的运动参数,建立人体运动参数与导航参数之间的映射模型,实现基于惯性测量信息/人体运动模型的行人自主导航。然后,利用超宽带提供的位置信息作为测量,设计基于惯性测量信息/人体运动模型/超宽带组合系统的卡尔曼滤波,将惯性测量信息/人体运动模型与超宽带组合系统的定位信息进行融合,为室内行人提供长期高精度的相对导航。本文开发了惯性测量信息/人体运动模型/超宽带组合系统的原型,为所提方法的实验验证提供了物理平台。并结合北京测量科技有限公司NOKOV高精度室内3d运动捕捉系统环境下的实验,对所提方法进行了优化和验证。该方法在单兵系统、城市反恐作战、行人定位等应急救援领域具有广阔的应用前景。
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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