文献类型：期刊文献

英文题名：Modeling of Structure Landmark for Indoor Pedestrian Localization

作者：Liu, Tao[1,2];Zhang, Xing[3,4,5,6];Li, Qingquan[3,4,5,6];Fang, Zhixiang[7]

第一作者：刘婷

通讯作者：Zhang, X[1];Zhang, X[2];Zhang, X[3]

机构：[1]Henan Univ Econ & Law, Coll Resources & Environm, Zhengzhou 450002, Henan, Peoples R China;[2]Henan Univ Econ & Law, Academician Lab Urban & Rural Spatial Data Min He, Zhengzhou 450002, Henan, Peoples R China;[3]Shenzhen Univ, Guangdong Key Lab Urban Informat, Shenzhen 518060, Peoples R China;[4]Shenzhen Univ, Shenzhen Key Lab Spatial Smart Sensing & Serv, Shenzhen 518060, Peoples R China;[5]Shenzhen Univ, Minist Nat Resources, Key Lab Geoenvironm Monitoring Coastal Zone, Shenzhen 518060, Peoples R China;[6]Shenzhen Univ, Sch Architecture & Urban Planning, Shenzhen 518060, Peoples R China;[7]Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430072, Hubei, Peoples R China

第一机构：河南财经政法大学资源与环境学院

通讯机构：[1]corresponding author), Shenzhen Univ, Guangdong Key Lab Urban Informat, Shenzhen 518060, Peoples R China;[2]corresponding author), Shenzhen Univ, Shenzhen Key Lab Spatial Smart Sensing & Serv, Shenzhen 518060, Peoples R China;[3]corresponding author), Shenzhen Univ, Minist Nat Resources, Key Lab Geoenvironm Monitoring Coastal Zone, Shenzhen 518060, Peoples R China.

年份：2019

卷号：7

起止页码：15654-15668

外文期刊名：IEEE ACCESS

收录：;EI(收录号：20190806530012);Scopus(收录号：2-s2.0-85061737293);WOS:【SCI-EXPANDED(收录号:WOS:000459413200001)】；

基金：This work was supported in part by the National Key Research Development Program of China under Grant 2016YFB0502203, in part by the National Science Foundation of China under Grant 41801376, Grant 41301511, and Grant 41771473, in part by the Natural Science Foundation of Guangdong Province under Grant 2018A030313289, in part by the Shenzhen Scientific Research and Development Funding Program under Grant JCYJ20170818144544900, in part by the Open Research Fund of the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, under Grant 18S03, in part by the Key Research Projects of Henan Higher Education Institutions under Grant 19A420004, and in part by the Open Research Fund Program of the Shenzhen Key Laboratory of Spatial Smart Sensing and Services (Shenzhen University), Research Program of Shenzhen S&T Innovation Committee, under Grant JCYJ20170412105839839.

语种：英文

外文关键词：Landmark; indoor structure; indoor localization

摘要：The decreasing of accumulative error is a key issue for various multi-sensor fusion-based indoor localization systems that employ pedestrian dead reckoning (PDR) to improve their localization performance. Current studies mainly use activity-based map matching (AMM) to prevent the accumulative error. However, it is vulnerable to mismatch problems, which are usually caused by the randomness of human activities. This paper proposes a structure landmark map matching-based indoor localization approach. Structure landmarks refer to special spatial structures (e.g., intersections, corridors, or corners), which are visually salient in a local environment. These landmarks are visually recognizable in indoor spaces because of their distinct shapes. This paper integrates visual and inertial information to recognize the structure landmarks by using a Bayesian classifier. An algorithm is also proposed to realize indoor localization without prior knowledge of the initial location or the turning angles of people. This approach decreases the accumulative localization error of PDR by matching the detected structure landmarks to the ground-truth values. The experimental results showed that the identification accuracy of the structure landmark was about 90% and the matching accuracy was 92%. The mean off-line localization error was about 1.2 m. Compared with the AMM-based method, this approach is robust to the random turning activities of people and can realize indoor localization with a faster convergence speed.