{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T17:13:09Z","timestamp":1781370789925,"version":"3.54.1"},"reference-count":34,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2022,10,25]],"date-time":"2022-10-25T00:00:00Z","timestamp":1666656000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Trade, Industry and Energy of Korea","award":["10063300"],"award-info":[{"award-number":["10063300"]}]},{"name":"the Open AI Dataset Project (AI-Hub, S. Korea)","award":["10063300"],"award-info":[{"award-number":["10063300"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Among existing wireless and wearable indoor pedestrian tracking solutions, the ultra-wideband (UWB) and inertial measurement unit (IMU) sensors are the popular options due to their accurate and globally referenced positioning, and low-cost and compact size, respectively. However, the UWB position accuracy is compromised by the indoor non-line of sight (NLOS) and the IMU estimation suffers from orientation drift as well as requiring position initialization. To overcome these limitations, this paper proposes a low-cost foot-placed UWB and IMU fusion-based indoor pedestrian tracking system. Our data fusion model is an improved loosely coupled Kalman filter with the inclusion of valid UWB observation detection. In this manner, the proposed system not only adjusts the consumer-grade IMU\u2019s accumulated drift but also filters out any NLOS instances in the UWB observation. We validated the performance of the proposed system with two experimental scenarios in a complex indoor environment. The root mean square (RMS) positioning accuracy of our data fusion model is enhanced by 60%, 53%, and 27% compared to that of the IMU-based pedestrian dead reckoning, raw UWB position, and conventional fusion model, respectively, in the single-lap NLOS scenario, and by 70%, 34%, and 12%, respectively, in the multi-lap LOS+NLOS scenario.<\/jats:p>","DOI":"10.3390\/s22218160","type":"journal-article","created":{"date-parts":[[2022,10,26]],"date-time":"2022-10-26T07:17:48Z","timestamp":1666768668000},"page":"8160","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["A Low-Cost Foot-Placed UWB and IMU Fusion-Based Indoor Pedestrian Tracking System for IoT Applications"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0820-3569","authenticated-orcid":false,"given":"Khawar","family":"Naheem","sequence":"first","affiliation":[{"name":"Center for Healthcare Robotics, School of Integrated Technology, Gwangju Institute of Science and Technology, Gwangju 61005, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6050-6594","authenticated-orcid":false,"given":"Mun Sang","family":"Kim","sequence":"additional","affiliation":[{"name":"Center for Healthcare Robotics, School of Integrated Technology, Gwangju Institute of Science and Technology, Gwangju 61005, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1121","DOI":"10.1109\/COMST.2020.2973314","article-title":"The Future of Healthcare Internet of Things: A Survey of Emerging Technologies","volume":"22","author":"Qadri","year":"2020","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"56094","DOI":"10.1109\/ACCESS.2022.3177278","article-title":"Emerging Technologies for Next Generation Remote Health Care and Assisted Living","volume":"10","author":"Ahmad","year":"2022","journal-title":"IEEE Access"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Khalil, U., Malik, O.A., Uddin, M., and Chen, C.-L. (2022). A Comparative Analysis on Blockchain versus Centralized Authentication Architectures for IoT-Enabled Smart Devices in Smart Cities: A Comprehensive Review, Recent Advances, and Future Research Directions. Sensors, 22.","DOI":"10.3390\/s22145168"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.cosrev.2017.03.002","article-title":"Indoor location based services challenges, requirements and usability of current solutions","volume":"24","author":"Basiri","year":"2017","journal-title":"Comput. Sci. Rev."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"48064","DOI":"10.1109\/ACCESS.2021.3065105","article-title":"Deep Neural Network-Based Double-Check Method for Fall Detection Using IMU-L Sensor and RGB Camera Data","volume":"9","author":"Lee","year":"2021","journal-title":"IEEE Access"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"857","DOI":"10.1007\/s40846-016-0184-2","article-title":"Evaluation of Kinect 3D Sensor for Healthcare Imaging","volume":"36","author":"Harkness","year":"2016","journal-title":"J. Med. Biol. Eng."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.patcog.2019.05.020","article-title":"RGB-D Sensing Based Human Action and Interaction Analysis: A Survey","volume":"94","author":"Liu","year":"2019","journal-title":"Pattern Recognit."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"14424","DOI":"10.1109\/JSEN.2022.3183887","article-title":"PINDOC: Pedestrian Indoor Navigation System Integrating Deterministic, Opportunistic, and Cooperative Functionalities","volume":"14","author":"Jao","year":"2022","journal-title":"IEEE Sens. J."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2104","DOI":"10.1109\/JSEN.2020.3017235","article-title":"A Novel Position and Orientation System for Pedestrian Indoor Mobile Mapping System","volume":"21","author":"Niu","year":"2021","journal-title":"IEEE Sens. J."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1109\/SURV.2009.090103","article-title":"A Survey of Indoor Positioning Systems for Wireless Personal Networks","volume":"11","author":"Gu","year":"2009","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Naheem, K., Elsharkawy, A., Koo, D., Lee, Y., and Kim, M. (2022). A UWB-Based Lighter-Than-Air Indoor Robot for User-Centered Interactive Applications. Sensors, 22.","DOI":"10.3390\/s22062093"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Elsharkawy, A., Naheem, K., Koo, D., and Kim, M.S. (2021). A UWB-Driven Self-Actuated Projector Platform for Interactive Augmented Reality Applications. Appl. Sci., 11.","DOI":"10.3390\/app11062871"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Zampella, F., Jimenez, R.A.R., and Seco, F. (2013, January 28\u201331). Robust Indoor Positioning Fusing PDR and RF Technologies: The RFID and UWB Case. Proceedings of the 2013 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Montbeliard-Belfort, France.","DOI":"10.1109\/IPIN.2013.6817857"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Barral, V., Escudero, C.J., Garc\u00eda-Naya, J.A., and Maneiro-Catoira, R. (2019). NLOS Identification and Mitigation Using Low-Cost UWB Devices. Sensors, 19.","DOI":"10.3390\/s19163464"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Jim\u00e9nez, A.R., and Seco, F. (2021). Improving the Accuracy of Decawave\u2019s UWB MDEK1001 Location System by Gaining Access to Multiple Ranges. Sensors, 21.","DOI":"10.3390\/s21051787"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"44413","DOI":"10.1109\/ACCESS.2022.3169267","article-title":"Precision positioning for smart logistics using ultra-wideband technology-based indoor navigation: A review","volume":"10","author":"Elsanhoury","year":"2022","journal-title":"IEEE Access"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1017\/S0373463308005043","article-title":"Heuristic Reduction of Gyro Drift in IMU-Based Personnel Tracking Systems","volume":"62","author":"Borenstein","year":"2008","journal-title":"J. Navig."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"6766","DOI":"10.1109\/JSEN.2016.2585599","article-title":"Step Detection for ZUPT-Aided Inertial Pedestrian Navigation System using Foot-Mounted Permanent Magnet","volume":"16","author":"Norrdine","year":"2016","journal-title":"IEEE Sens. J."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"8953","DOI":"10.1109\/JIOT.2021.3119328","article-title":"Real-Time Human Motion Capture Based on Wearable Inertial Sensor Networks","volume":"9","author":"Li","year":"2022","journal-title":"IEEE Internet Things J."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Eskofier, B.M., Lee, S.I., Baron, M., Simon, A., Martindale, C.F., Ga\u00dfner, H., and Klucken, J. (2017). An Overview of Smart Shoes in the Internet of Health Things: Gait and Mobility Assessment in Health Promotion and Disease Monitoring. Appl. Sci., 7.","DOI":"10.3390\/app7100986"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Corrales Ram\u00f3n, J.A., Candelas-Her\u00edas, F.A., and Torres, F. (2008, January 12\u201315). Hybrid Tracking of Human Operators Using IMU\/UWB Data Fusion by a Kalman Filter. Proceedings of the 2008 3rd ACM\/IEEE International Conference on Human-Robot Interaction (HRI), Amsterdam, The Netherlands.","DOI":"10.1145\/1349822.1349848"},{"key":"ref_22","unstructured":"Hol, J.D., Dijkstra, F., Luinge, H.J., and Slycke, P.J. (2011). Tightly Coupled UWB\/IMU Pose Estimation System and Method. (US 2011\/0025562 A1), US Patent."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1109\/MPRV.2012.16","article-title":"Tutorial: Implementing a Pedestrian Tracker Using Inertial Sensors","volume":"12","author":"Fischer","year":"2013","journal-title":"IEEE Pervasive Comput."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"927","DOI":"10.1109\/TSMC.2016.2521823","article-title":"A Novel Biomechanical Model-Aided IMU\/UWB Fusion for Magnetometer-Free Lower Body Motion Capture","volume":"47","author":"Zihajehzadeh","year":"2016","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"3577","DOI":"10.1109\/TIM.2015.2459532","article-title":"UWB-Aided Inertial Motion Capture for Lower Body 3-D Dynamic Activity and Trajectory Tracking","volume":"64","author":"Zihajehzadeh","year":"2015","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Zhang, H., Zhang, Z., Gao, N., Xiao, Y., Meng, Z., and Li, Z. (2020). Cost-Effective Wearable Indoor Localization and Motion Analysis via the Integration of UWB and IMU. Sensors, 20.","DOI":"10.3390\/s20020344"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"14401","DOI":"10.1109\/JSEN.2020.2998815","article-title":"UWB\/INS Integrated Pedestrian Positioning for Robust Indoor Environments","volume":"20","author":"Zhang","year":"2020","journal-title":"IEEE Sens. J."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Nilsson, J.O., Rantakokko, J., H\u00e4ndel, P., Skog, I., Ohlsson, M., and Hari, K.V.S. (2014, January 5\u20138). Accurate Indoor Positioning of Firefighters using Dual Foot-mounted Inertial Sensors and Inter-agent Ranging. Proceedings of the 2014 IEEE\/ION Position, Location and Navigation Symposium (PLANS), Monterey, CA, USA.","DOI":"10.1109\/PLANS.2014.6851424"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"952","DOI":"10.1109\/JAS.2019.1911570","article-title":"Indoor INS\/UWB-based Human Localization with Missing Data Utilizing Predictive UFIR Filtering","volume":"6","author":"Xu","year":"2019","journal-title":"IEEE\/CAA J. Autom. Sin."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"16676","DOI":"10.1109\/ACCESS.2017.2743213","article-title":"UWB-Based Indoor Human Localization with Time-Delayed Data Using EFIR Filtering","volume":"5","author":"Xu","year":"2017","journal-title":"IEEE Access"},{"key":"ref_31","unstructured":"(2022, July 19). MDEK1001 Development Kit. Available online: https:\/\/www.qorvo.com\/products\/p\/MDEK1001."},{"key":"ref_32","unstructured":"(2022, July 19). Purchase Website of MDEK1001. Available online: https:\/\/www.symmetryelectronics.com\/products\/decawave-now-qorvo\/mdek1001\/."},{"key":"ref_33","unstructured":"(2022, July 19). Online Shopping Website. Available online: https:\/\/www.coupang.com\/."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Nilsson, J.O., Skog, I., Handel, P., and Hari, K. (2012, January 23\u201326). Foot-Mounted INS for Everybody\u2014An Open-Source Embedded Implementation. Proceedings of 2012 IEEE\/ION Position Location and Navigation Symposium (PLANS), Myrtle Beach, SC, USA.","DOI":"10.1109\/PLANS.2012.6236875"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/21\/8160\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:02:14Z","timestamp":1760144534000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/21\/8160"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,25]]},"references-count":34,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2022,11]]}},"alternative-id":["s22218160"],"URL":"https:\/\/doi.org\/10.3390\/s22218160","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,25]]}}}