文献类型：期刊文献

英文题名：An Accurate Visual-Inertial Integrated Geo-Tagging Method for Crowdsourcing-Based Indoor Localization

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

通讯作者：Zhang, X[1];Zhang, X[2]

机构：[1]Henan Univ Econ & Law, Coll Resources & Environm, Zhengzhou 450002, Henan, Peoples R China;[2]Shenzhen Univ, Shenzhen Key Lab Spatial Informat Smart Sensing &, Sch Architecture & Urban Planning, Natl Adm Surveying Mapping & GeoInformat, Shenzhen 518060, Peoples R China;[3]Shenzhen Univ, Key Lab Geoenvironm Monitoring Coastal Zone, Sch Architecture & Urban Planning, Natl Adm Surveying Mapping & GeoInformat, Shenzhen 518060, Peoples R China;[4]Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430072, Hubei, Peoples R China;[5]Henan Agr Univ, Coll Mech & Elect Engn, Zhengzhou 450002, Henan, 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, Shenzhen Key Lab Spatial Informat Smart Sensing &, Sch Architecture & Urban Planning, Natl Adm Surveying Mapping & GeoInformat, Shenzhen 518060, Peoples R China;[2]corresponding author), Shenzhen Univ, Key Lab Geoenvironm Monitoring Coastal Zone, Sch Architecture & Urban Planning, Natl Adm Surveying Mapping & GeoInformat, Shenzhen 518060, Peoples R China.

年份：2019

卷号：11

期号：16

外文期刊名：REMOTE SENSING

收录：;EI(收录号：20193607396469);Scopus(收录号：2-s2.0-85071560742);WOS:【SCI-EXPANDED(收录号:WOS:000484387600075)】；

基金：This research was funded by National Science Foundation of China (grants 41801376, 41301511, 41771473), National Key Research Development Program of China (2016YFB0502203), Natural Science Foundation of Guangdong Province (2018A030313289), Shenzhen Scientific Research and Development Funding Program (JCYJ20170818144544900, JCYJ20180305125033478), Open Research Fund of state key laboratory of information engineering in surveying, mapping and remote sensing, Wuhan University (18S03). Key Research Projects of Henan Higher Education Institutions (19A420004). Open Research Fund Program of Shenzhen Key Laboratory of Spatial Smart Sensing and Services (Shenzhen University).

语种：英文

外文关键词：indoor localization; crowdsourcing trajectory; fingerprinting; smartphone

摘要：One of the unavoidable bottlenecks in the public application of passive signal (e.g., received signal strength, magnetic) fingerprinting-based indoor localization technologies is the extensive human effort that is required to construct and update database for indoor positioning. In this paper, we propose an accurate visual-inertial integrated geo-tagging method that can be used to collect fingerprints and construct the radio map by exploiting the crowdsourced trajectory of smartphone users. By integrating multisource information from the smartphone sensors (e.g., camera, accelerometer, and gyroscope), this system can accurately reconstruct the geometry of trajectories. An algorithm is proposed to estimate the spatial location of trajectories in the reference coordinate system and construct the radio map and geo-tagged image database for indoor positioning. With the help of several initial reference points, this algorithm can be implemented in an unknown indoor environment without any prior knowledge of the floorplan or the initial location of crowdsourced trajectories. The experimental results show that the average calibration error of the fingerprints is 0.67 m. A weighted k-nearest neighbor method (without any optimization) and the image matching method are used to evaluate the performance of constructed multisource database. The average localization error of received signal strength (RSS) based indoor positioning and image based positioning are 3.2 m and 1.2 m, respectively, showing that the quality of the constructed indoor radio map is at the same level as those that were constructed by site surveying. Compared with the traditional site survey based positioning cost, this system can greatly reduce the human labor cost, with the least external information.