{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T10:00:54Z","timestamp":1781949654187,"version":"3.54.5"},"reference-count":47,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2018,10,3]],"date-time":"2018-10-03T00:00:00Z","timestamp":1538524800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key Research and Development Program","award":["2018YFB0505200"],"award-info":[{"award-number":["2018YFB0505200"]}]},{"name":"the BUPT Excellent Ph.D. Students Foundation","award":["CX2018102"],"award-info":[{"award-number":["CX2018102"]}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61671264"],"award-info":[{"award-number":["61671264"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61671077"],"award-info":[{"award-number":["61671077"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/s18103317","type":"journal-article","created":{"date-parts":[[2018,10,4]],"date-time":"2018-10-04T02:19:49Z","timestamp":1538619589000},"page":"3317","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["An Infrastructure-Free Indoor Localization Algorithm for Smartphones"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6551-6807","authenticated-orcid":false,"given":"Qu","family":"Wang","sequence":"first","affiliation":[{"name":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunication, Beijing 100876, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6827-4225","authenticated-orcid":false,"given":"Haiyong","family":"Luo","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aidong","family":"Men","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunication, Beijing 100876, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fang","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Software Engineering, Beijing University of Posts and Telecommunication, Beijing 100876, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Huang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Advanced Optical Communication Systems and Networks, Peking University, Beijing 100871, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,10,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1443","DOI":"10.1109\/JSAC.2015.2430274","article-title":"Magicol: Indoor Localization Using Pervasive Magnetic Field and Opportunistic WiFi Sensing","volume":"33","author":"Shu","year":"2015","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_2","unstructured":"(2018, October 01). Indoor Location Market worth 40.99 Billion USD by 2022. Available online: https:\/\/www.marketsand markets.com\/PressReleases\/indoor-location.asp."},{"key":"ref_3","unstructured":"Bahl, P., and Padmanabhan, V.N. (2000, January 26\u201330). RADAR: An in-building RF-based user location and tracking system. Proceedings of the Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE INFOCOM 2000), Tel Aviv, Israel."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Liu, H.-H., and Liu, C. (2017). Implementation of Wi-Fi Signal Sampling on an Android Smartphone for Indoor Positioning Systems. Sensors, 18.","DOI":"10.3390\/s18010003"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Tiemann, J., Pillmann, J., and Wietfeld, C. (2017, January 4\u20137). Ultra-Wideband Antenna-Induced Error Prediction Using Deep Learning on Channel Response Data. Proceedings of the 2017 IEEE 85th Vehicular Technology Conference (VTC Spring), Sydney, Australia.","DOI":"10.1109\/VTCSpring.2017.8108571"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Yohan, A., Lo, N.-W., and Winata, D. (2018). An Indoor Positioning-Based Mobile Payment System Using Bluetooth Low Energy Technology. Sensors, 18.","DOI":"10.3390\/s18040974"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Liu, T., Zhang, X., Li, Q., and Fang, Z. (2017). A Visual-Based Approach for Indoor Radio Map Construction Using Smartphones. Sensors, 17.","DOI":"10.3390\/s17081790"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Li, Z., Feng, L., and Yang, A. (2017). Fusion Based on Visible Light Positioning and Inertial Navigation Using Extended Kalman Filters. Sensors, 17.","DOI":"10.3390\/s17051093"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Alonso-Gonz\u00e1lez, I., S\u00e1nchez-Rodr\u00edguez, D., Ley-Bosch, C., and Quintana-Su\u00e1rez, M. (2018). Discrete Indoor Three-Dimensional Localization System Based on Neural Networks Using Visible Light Communication. Sensors, 18.","DOI":"10.3390\/s18041040"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1007\/s11276-016-1312-1","article-title":"LiPro: Light-based indoor positioning with rotating handheld devices","volume":"24","author":"Xie","year":"2018","journal-title":"Wirel. Netw."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Kuo, Y., Pannuto, P., Hsiao, K., Dutta, P., and Arbor, A. (2014, January 7\u201311). Luxapose: Indoor Positioning with Mobile Phones and Visible Light. Proceedings of the 20th Annual International Conference on Mobile Computing and Networking (Mobicom \u201914), Maui, HI, USA.","DOI":"10.1145\/2639108.2639109"},{"key":"ref_12","unstructured":"Li, L., Hu, P., Peng, C., Shen, G., and Zhao, F. (2014, January 2\u20134). Epsilon: A Visible Light Based Positioning System. Proceedings of the 11th USENIX Conference on Networked Systems Design and Implementation, Seattle, WA, USA."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Xu, Q., Zheng, R., and Hranilovic, S. (2015, January 7\u201311). IDyLL: Indoor Localization using Inertial and Light Sensors on Smartphones. Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp \u201915), Osaka, Japan.","DOI":"10.1145\/2750858.2807540"},{"key":"ref_14","first-page":"1550147718758263","article-title":"Light positioning: A high-accuracy visible light indoor positioning system based on attitude identification and propagation model","volume":"14","author":"Wang","year":"2018","journal-title":"Int. J. Distrib. Sens. Netw."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Hu, P., Li, L., Peng, C., Shen, G., and Zhao, F. (2013, January 21\u201322). Pharos: Enable Physical Analytics Through Visible Light Based Indoor Localization. Proceedings of the Twelfth ACM Workshop on Hot Topics in Networks (HotNets-XII), College Park, MD, USA.","DOI":"10.1145\/2535771.2535790"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Huynh, P., and Yoo, M. (2016). VLC-Based Positioning System for an Indoor Environment Using an Image Sensor and an Accelerometer Sensor. Sensors, 16.","DOI":"10.3390\/s16060783"},{"key":"ref_17","unstructured":"(2018, October 01). Energy Savings Forecast of Solid-State Lighting in General Illumination Applications. Available online: https:\/\/nlb.org\/energy-savings-forecast-of-solid-state-lighting-in-general-illumination-applications\/."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Jim\u00e9nez, A.R., Zampella, F., and Seco, F. (2013, January 28\u201331). Light-matching: A new signal of opportunity for pedestrian indoor navigation. Proceedings of the 4th International Conference on Indoor Positioning and Indoor Navigation (IPIN 2013), Montbeliard-Belfort, France.","DOI":"10.1109\/IPIN.2013.6817843"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Zhang, C., and Zhang, X. (2016, January 3\u20137). LiTell. Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking (MobiCom \u201916), New York, NY, USA.","DOI":"10.1145\/2973750.2973767"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Zhu, S., and Zhang, X. (2017, January 19\u201323). Enabling High-Precision Visible Light Localization in Today\u2019s Buildings. Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services (MobiSys \u201917), Niagara Falls, NY, USA.","DOI":"10.1145\/3081333.3081335"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Zhao, Z., Wang, J., Zhao, X., Peng, C., Guo, Q., and Wu, B. (2017, January 1\u20134). NaviLight: Indoor localization and navigation under arbitrary lights. Proceedings of the 36th IEEE International Conference on Computer Communications (INFOCOM 2017), Atlanta, GA, USA.","DOI":"10.1109\/INFOCOM.2017.8057184"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Kim, D.-R., Yang, S.-H., Kim, H.-S., Son, Y.-H., and Han, S.-K. (2012, January 1\u20133). Outdoor visible light communication for inter-vehicle communication using controller area network. Proceedings of the 2012 4th International Conference on Communications and Electronics (ICCE 2012), Hue, Vietnam.","DOI":"10.1109\/CCE.2012.6315865"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Ilyas, M., Cho, K., Baeg, S.-H., and Park, S. (2016). Drift Reduction in Pedestrian Navigation System by Exploiting Motion Constraints and Magnetic Field. Sensors, 16.","DOI":"10.3390\/s16091455"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1945695","DOI":"10.1155\/2016\/1945695","article-title":"Location Fingerprint Extraction for Magnetic Field Magnitude Based Indoor Positioning","volume":"2016","author":"Shao","year":"2016","journal-title":"J. Sens."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Xie, H., Gu, T., Tao, X., Ye, H., and Lv, J. (2014, January 13\u201317). MaLoc: A Practical Magnetic Fingerprinting Approach to Indoor Localization using Smartphones Hongwei. Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp \u201914), Seattle, WA, USA.","DOI":"10.1145\/2632048.2632057"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1877","DOI":"10.1109\/TMC.2015.2480064","article-title":"A Reliability-Augmented Particle Filter for Magnetic Fingerprinting Based Indoor Localization on Smartphone","volume":"15","author":"Xie","year":"2016","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Wang, Q., Luo, H., Zhao, F., and Shao, W. (2016, January 4\u20137). An indoor self-localization algorithm using the calibration of the online magnetic fingerprints and indoor landmarks. Proceedings of the 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN 2016), Madrid, Spain.","DOI":"10.1109\/IPIN.2016.7743595"},{"key":"ref_28","unstructured":"Chung, J., Donahoe, M., Schmandt, C., Kim, I.-J., Razavai, P., and Wiseman, M. (July, January 28). Indoor location sensing using geo-magnetism. Proceedings of the 9th International Conference on Mobile Systems, Applications, and Services (MobiSys \u201911), Bethesda, MD, USA."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Angermann, M., Frassl, M., Doniec, M., Julian, B.J., and Robertson, P. (2012, January 13\u201315). Characterization of the indoor magnetic field for applications in Localization and Mapping. Proceedings of the 2012 International Conference on Indoor Positioning and Indoor Navigation (IPIN 2012), Sydney, Australia.","DOI":"10.1109\/IPIN.2012.6418864"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Storms, W., Shockley, J., and Raquet, J. (2010, January 14\u201315). Magnetic field navigation in an indoor environment. Proceedings of the 2010 Ubiquitous Positioning Indoor Navigation and Location Based Service (UPINLBS 2010), Helsinki, Finland.","DOI":"10.1109\/UPINLBS.2010.5653681"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"935","DOI":"10.1109\/TIM.2017.2682738","article-title":"Magnetic Field Analysis for 3-D Positioning Applications","volume":"66","author":"Pasku","year":"2017","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1770","DOI":"10.1109\/TMC.2015.2478451","article-title":"SemanticSLAM: Using Environment Landmarks for Unsupervised Indoor Localization","volume":"15","author":"Abdelnasser","year":"2016","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"3883","DOI":"10.1109\/TIM.2011.2147690","article-title":"Magnetic maps for indoor navigation","volume":"60","author":"Gozick","year":"2011","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1145\/2508037.2508054","article-title":"LocateMe: Magnetic-fields-based indoor localization using smartphones","volume":"4","author":"Subbu","year":"2013","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1109\/TMC.2014.2319824","article-title":"GROPING: Geomagnetism and crowdsensing powered indoor navigation","volume":"14","author":"Zhang","year":"2015","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Luo, H., Zhao, F., Jiang, M., Ma, H., and Zhang, Y. (2017). Constructing an Indoor Floor Plan Using Crowdsourcing Based on Magnetic Fingerprinting. Sensors, 17.","DOI":"10.3390\/s17112678"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"874","DOI":"10.1109\/TMM.2016.2636750","article-title":"Fusion of Magnetic and Visual Sensors for Indoor Localization: Infrastructure-Free and More Effective","volume":"19","author":"Liu","year":"2017","journal-title":"IEEE Trans. Multimed."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"2286","DOI":"10.1109\/TMC.2015.2398431","article-title":"Indoor tracking using undirected graphical models","volume":"14","author":"Xiao","year":"2015","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_39","unstructured":"Rallapalli, S. (2014). Mobile Localization: Approach and Applications, The University of Texas at Austin."},{"key":"ref_40","first-page":"265","article-title":"Ubiquitous Positioning: A Taxonomy for Location Determination on Mobile Navigation System","volume":"85","author":"Bejuri","year":"2011","journal-title":"Proc. IEEE"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Li, B., Gallagher, T., Dempster, A.G., and Rizos, C. (2012, January 13\u201315). How feasible is the use of magnetic field alone for indoor positioning?. Proceedings of the 2012 International Conference on Indoor Positioning and Indoor Navigation (IPIN 2012), Sydney, Australia.","DOI":"10.1109\/IPIN.2012.6418880"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Shu, Y., Shin, K.G., He, T., and Chen, J. (2015, January 7\u201311). Last-Mile Navigation Using Smartphones. Proceedings of the 21st Annual International Conference on Mobile Computing and Networking (MobiCom \u201914), Paris, France.","DOI":"10.1145\/2789168.2790099"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Zhou, P., Li, M., and Shen, G. (2014, January 7\u201311). Use it free. Proceedings of the 20th Annual International Conference on Mobile Computing and Networking, Maui, HI, USA.","DOI":"10.1145\/2639108.2639110"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Kang, W., Nam, S., Han, Y., and Lee, S. (2012, January 9\u201312). Improved heading estimation for smartphone-based indoor positioning systems. Proceedings of the IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, Sydney, Australia.","DOI":"10.1109\/PIMRC.2012.6362768"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"3453","DOI":"10.1109\/JSEN.2017.2685999","article-title":"Robust and Accurate Smartphone-Based Step Counting for Indoor Localization","volume":"17","author":"Gu","year":"2017","journal-title":"IEEE Sens. J."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1600","DOI":"10.1109\/JSEN.2017.2776100","article-title":"Probabilistic Context-Aware Step Length Estimation for Pedestrian Dead Reckoning","volume":"18","author":"Martinelli","year":"2018","journal-title":"IEEE Sens. J."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1109\/TII.2015.2491264","article-title":"HYFI: Hybrid Floor Identification Based on Wireless Fingerprinting and Barometric Pressure","volume":"13","author":"Zhao","year":"2017","journal-title":"IEEE Trans. Ind. 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