陈锐志, 叶锋. 基于Wi-Fi信道状态信息的室内定位技术现状综述[J]. 武汉大学学报 ( 信息科学版), 2018, 43(12): 2064-2070. DOI: 10.13203/j.whugis20180176
引用本文: 陈锐志, 叶锋. 基于Wi-Fi信道状态信息的室内定位技术现状综述[J]. 武汉大学学报 ( 信息科学版), 2018, 43(12): 2064-2070. DOI: 10.13203/j.whugis20180176
CHEN Ruizhi, YE Feng. An Overview of Indoor Positioning Technology Based on Wi-Fi Channel State Information[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12): 2064-2070. DOI: 10.13203/j.whugis20180176
Citation: CHEN Ruizhi, YE Feng. An Overview of Indoor Positioning Technology Based on Wi-Fi Channel State Information[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12): 2064-2070. DOI: 10.13203/j.whugis20180176

基于Wi-Fi信道状态信息的室内定位技术现状综述

An Overview of Indoor Positioning Technology Based on Wi-Fi Channel State Information

  • 摘要: 室内定位技术一直是工业界和学术界的研究热点,Wi-Fi信号作为重要的定位源,长期受到研究人员的关注。传统的利用接收信号强度的Wi-Fi定位方法受到诸多限制,容易受到环境等因素的影响,精度难以有效提升,也无法展开大规模的应用。信道状态信息(channel state information,CSI)是一种比接收信号强度更能描述Wi-Fi信号传播本质的观测量,利用CSI进行室内定位研究已得到越来越多的关注。介绍了CSI基本概念,综述了现有基于CSI的各类定位方法,包括指纹匹配、测角和测距等,分别描述其基本原理,指出其中的优缺点,并分析其现状和难点。并对基于Wi-Fi信道状态信息的定位技术未来的发展方向进行了展望。

     

    Abstract: Indoor positioning is currently a research hot topic for industrial and scientific communities. Wi-Fi signal has been a common positioning signal adapted researchers. Received signal strength indicator is a traditional measurement used for indoor positioning. It can be easily affected by many factors such as the change of environment. Therefore, it is difficult to achieve such an accuracy that can be used in practice and hard to deploy the positioning solution in a large-scale. More and more resear-chers are now focusing on using channel state information as the measurement, which contains an essential description of Wi-Fi signal propagation and provides more details about the communication channel. This information can be transformed to a useful measurement for positioning. In this paper, we introduce the fundamental description of channel state information and classify the positioning approaches into three categories, which are fingerprinting-based, angle of arrival-based and ranging-based, respectively. The current states of these technologies have been reviewed in details, and the pros and cons have been identified and compared. We conclude the paper with a discussion about the directions in this field.

     

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