测绘学报 ›› 2019, Vol. 48 ›› Issue (12): 1498-1506.doi: 10.11947/j.AGCS.2019.20190455

• 综述 • 上一篇    下一篇

GIS辅助的室内定位技术研究进展

李清泉1,2,3, 周宝定1,3, 马威1,3, 薛卫星1,3   

  1. 1. 深圳大学广东省城市空间信息工程重点实验室, 广东 深圳 518060;
    2. 人工智能与数字经济广东省实验室(深圳), 广东 深圳 518060;
    3. 深圳大学土木与交通工程学院, 广东 深圳 518060
  • 收稿日期:2019-11-03 修回日期:2019-11-08 发布日期:2019-12-24
  • 通讯作者: 周宝定 E-mail:bdzhou@szu.edu.cn
  • 作者简介:李清泉(1965-),男,教授,博士生导师,研究方向为动态精密工程测量。E-mail:liqq@szu.edu.cn
  • 基金资助:
    国家重点研发计划(2016YFB0502203);国家自然科学基金(41701519);深圳市科技计划项目(JCYJ20180305125058727);广东省基础与应用基础研究基金(2019A1515011910)

Research process of GIS-aided indoor localization

LI Qingquan1,2,3, ZHOU Baoding1,3, MA Wei1,3, XUE Weixing1,3   

  1. 1. Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen 518060, China;
    2. Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ), Shenzhen University, Shenzhen 518060, China;
    3. College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, China
  • Received:2019-11-03 Revised:2019-11-08 Published:2019-12-24
  • Supported by:
    The National Key Research and Development Program of China (No. 2016YFB0502203);The National Natural Science Foundation of China (No. 41701519);The Shenzhen Scientific Research and Development Funding Program (No. JCYJ20180305125058727);The Guangdong Basic and Applied Basic Research Foundation(No.2019A1515011910)

摘要: 室内定位技术是目前基于位置服务领域的研究热点之一,已引起政府部门、产业界和学术界的重视。室内GIS包含了丰富的先验知识,可用于辅助室内定位。本文对GIS辅助的室内定位技术需求、发展现状及面临的挑战进行了较系统梳理。首先介绍其发展现状,包括基于地图约束的室内定位、基于拓扑地图匹配的室内定位、基于语义感知的室内定位以及基于视觉感知的室内定位。随后,介绍了其面临的挑战,主要包括统一时空基准下的室内GIS数据模型、室内GIS数据更新以及智能手机有限的计算资源。最后,展望了其发展趋势,在GIS辅助的室内定位方面,将从基于语义感知的室内定位发展到基于空间认知的室内定位;在室内GIS数据的获取方面,将从目前的基于机器采集发展到人机交互式数据采集。

关键词: 室内定位, 室内GIS, 位置服务

Abstract: Indoor localization technology is one of the hot research topics in the field of location-based service (LBS), which has attracted the attention of government, industry and academia. Indoor GIS contains abundant priori knowledge, which can be used for indoor localization. In this paper, we review the research process of GIS-aided indoor localization. We first introduce the state-of-the-art, including map constraints-based indoor localization, topological map matching-based indoor localization, context sensing-based indoor localization, and visual sensing-based indoor localization. Then, we introduce its challenges, including indoor GIS data model in uniform space-time reference, data updating of indoor GIS, and limited computing resource of smartphones. Finally, we forecast the development trend in terms of GIS-aided indoor localization, it will develop from context sensing-based method to spatial cognition-based method. In the aspect of GIS data acquisition, it will develop from machine-based method to human-machine interaction-based method.

Key words: indoor localization, indoor GIS, location-based service

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