An Infrastructure-Free Indoor Localization Algorithm for Smartphones

doi:10.3390/s18103317

	An Infrastructure-Free Indoor Localization Algorithm for Smartphones
	Wang, Qu 1; Luo, Haiyong 2; Men, Aidong 1; Zhao, Fang 3; Huang, Yan 4
	2018-10-01
发表期刊	SENSORS
ISSN	1424-8220
卷号	18 期号:10 页码:24
摘要	Accurate indoor positioning technology provides location-based service for a variety of applications. However, most existing indoor localization approaches (e.g., Wi-Fi and Bluetooth-based methods) rely heavily on positioning infrastructure, which prevents their large-scale deployment and limits the range at which they are applicable. Here, we proposed an infrastructure-free indoor positioning and tracking approach, termed LiMag, which used ubiquitous magnetic field and ambient lights (e.g., fluorescent, incandescent, and light-emitting diodes (LEDs)) without containing modulated information. We conducted an in-depth study on both the advantages and the challenges in leveraging magnetic field and ambient light intensity for indoor localization. Based on the insights from this study, we established a hybrid observation model that took full advantage of both the magnetic field and ambient light signals. To address the low discernibility of the hybrid observation model, LiMag first generated a single-step fingerprint model by vectorizing consecutive hybrid observations within each step. In order to accurately track users, a lightweight single-step tracking algorithm based on the single-step fingerprints and the particle filter framework was designed. LiMag leveraged the walking information of users and several single-step fingerprints to generate long trajectory fingerprints that exhibited much higher location differentiation ability than the single-step fingerprint. To accelerate particle convergence and eliminate the accumulative error of single-step tracking algorithm, a long trajectory calibration scheme based on long trajectory fingerprints was also introduced. An undirected weighted graph model was constructed to decrease the computational overhead resulting from this long trajectory matching. In addition to typical indoor scenarios including offices, shopping malls and parking lots, we also conducted experiments in more challenging scenarios, including large open-plan areas as well as environments characterized by strong sunlight. Our proposed algorithm achieved a 75th percentile localization accuracy of 1.8 m and 2.2 m, respectively, in the office and shopping mall tested. In conclusion, our LiMag algorithm provided location-based service of infrastructure-free with significantly improved localization accuracy and coverage, as well as satisfactory robustness inside complex indoor environments.
关键词	indoor positioning visible light magnetic field fingerprints matching smartphone
DOI	10.3390/s18103317
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program[2018YFB0505200] ; BUPT Excellent Ph.D. Students Foundation[CX2018102] ; National Natural Science Foundation of China[61872046] ; National Natural Science Foundation of China[61671264] ; National Natural Science Foundation of China[61671077]
WOS研究方向	Chemistry ; Electrochemistry ; Instruments & Instrumentation
WOS类目	Chemistry, Analytical ; Electrochemistry ; Instruments & Instrumentation
WOS记录号	WOS:000448661500145
出版者	MDPI
引用统计	被引频次：15[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/4346
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Luo, Haiyong
作者单位	1.Beijing Univ Posts & Telecommun, Sch Informat & Commun Engn, Beijing 100876, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing Key Lab Mobile Comp & Pervas Device, Beijing 100190, Peoples R China 3.Beijing Univ Posts & Telecommun, Sch Software Engn, Beijing 100876, Peoples R China 4.Peking Univ, State Key Lab Adv Opt Commun Syst & Networks, Beijing 100871, Peoples R China
推荐引用方式 GB/T 7714	Wang, Qu,Luo, Haiyong,Men, Aidong,et al. An Infrastructure-Free Indoor Localization Algorithm for Smartphones[J]. SENSORS,2018,18(10):24.
APA	Wang, Qu,Luo, Haiyong,Men, Aidong,Zhao, Fang,&Huang, Yan.(2018).An Infrastructure-Free Indoor Localization Algorithm for Smartphones.SENSORS,18(10),24.
MLA	Wang, Qu,et al."An Infrastructure-Free Indoor Localization Algorithm for Smartphones".SENSORS 18.10(2018):24.