{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T19:19:00Z","timestamp":1776885540049,"version":"3.51.2"},"reference-count":43,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2020,6,8]],"date-time":"2020-06-08T00:00:00Z","timestamp":1591574400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Science and Technology Program of Guangzhou, China","award":["201803030045"],"award-info":[{"award-number":["201803030045"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61903145"],"award-info":[{"award-number":["61903145"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2018A030310395"],"award-info":[{"award-number":["2018A030310395"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Since widespread applications of wireless sensors networks, low-speed traffic positioning based on the received signal strength indicator (RSSI) from personal devices with WiFi broadcasts has attracted considerable attention. This study presents a new range-based localization method for outdoor pedestrian positioning by using the combination of offline RSSI distance estimation and real-time continuous position fitting, which can achieve high-position accuracy in the urban road environment. At the offline stage, the piecewise polynomial regression model (PPRM) is proposed to formulate the Euclidean distance between the targets and WiFi scanners by replacing the common propagation model (PM). The online stage includes three procedures. Firstly, a constant velocity Kalman filter (CVKF) is developed to smooth the real-time RSSI time series and estimate the target-detector distance. Then, a least squares Taylor series expansion (LS-TSE) is developed to calculate the actual 2-dimensional coordinate with the replacement of existing trilateral localization. Thirdly, a trajectory-based technique of the unscented Kalman filter (UKF) is introduced to smooth estimated positioning points. In tests that used field scenarios from Guangzhou, China, the experiments demonstrate that the combined CVKF and PPRM can achieve the highly accurate distance estimator of &lt;1.98 m error with the probability of 90% or larger, which outperforms the existing propagation model. In addition, the online method can achieve average positioning error of 1.67 m with the much better than classical methods.<\/jats:p>","DOI":"10.3390\/s20113259","type":"journal-article","created":{"date-parts":[[2020,6,9]],"date-time":"2020-06-09T06:34:16Z","timestamp":1591684456000},"page":"3259","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Multi-Stage Pedestrian Positioning Using Filtered WiFi Scanner Data in an Urban Road Environment"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3754-4821","authenticated-orcid":false,"given":"Zilin","family":"Huang","sequence":"first","affiliation":[{"name":"School of Civil Engineering and Transportation, South China University of Technology, No.381, Wushan Road, Guangzhou 510641, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lunhui","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Civil Engineering and Transportation, South China University of Technology, No.381, Wushan Road, Guangzhou 510641, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6263-7187","authenticated-orcid":false,"given":"Yongjie","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Civil Engineering and Transportation, South China University of Technology, No.381, Wushan Road, Guangzhou 510641, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.trc.2015.08.010","article-title":"Assessment of antenna characteristic effects on pedestrian and cyclists travel-time estimation based on Bluetooth and WiFi MAC addresses","volume":"60","author":"Abedi","year":"2015","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"892","DOI":"10.1109\/TBME.2013.2291910","article-title":"Self-contained pedestrian tracking during normal walking using an inertial\/magnetic sensor module","volume":"61","author":"Meng","year":"2014","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"4562","DOI":"10.1109\/TIE.2012.2216235","article-title":"Dynamic ultrasonic hybrid localization system for indoor mobile robots","volume":"60","author":"Kim","year":"2013","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1993","DOI":"10.1109\/TIE.2013.2266076","article-title":"Robust least squares approach to passive target localization using ultrasonic receiver array","volume":"61","author":"Choi","year":"2014","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"5914","DOI":"10.1109\/TIE.2012.2230596","article-title":"Efficient object localization using sparsely distributed passive RFID tags","volume":"60","author":"Yang","year":"2013","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1109\/JSTSP.2018.2796446","article-title":"Deep Learning for RF Device Fingerprinting in Cognitive Communication Networks","volume":"12","author":"Merchant","year":"2018","journal-title":"IEEE J. Sel. Top. Signal Process."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1756","DOI":"10.1109\/TSP.2009.2036060","article-title":"Low complexity location fingerprinting with generalized UWB energy detection receivers","volume":"58","author":"Steiner","year":"2010","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2260","DOI":"10.1109\/TCSVT.2016.2581660","article-title":"A Low-Complexity Pedestrian Detection Framework for Smart Video Surveillance Systems","volume":"27","author":"Bilal","year":"2017","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Leung, L., and Liang, J. (2019). Psychological traits, addiction symptoms, and feature usage as predictors of problematic smartphone use among university students in China. Substance Abuse and Addiction: Breakthroughs in Research and Practice, IGI Global.","DOI":"10.4018\/978-1-5225-7666-2.ch017"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"8841","DOI":"10.1109\/TVT.2016.2517151","article-title":"A Novel TOA-Based Mobile Localization Technique under Mixed LOS\/NLOS Conditions for Cellular Networks","volume":"65","author":"Zhou","year":"2016","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Zhuang, Y., Yang, J., Li, Y., Qi, L., and El-Sheimy, N. (2016). Smartphone-based indoor localization with bluetooth low energy beacons. Sensors, 16.","DOI":"10.3390\/s16050596"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"536","DOI":"10.1109\/WCL.2012.072012.120428","article-title":"On received-signal-strength based localization with unknown transmit power and path loss exponent","volume":"1","author":"Wang","year":"2012","journal-title":"IEEE Wirel. Commun. Lett."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"896","DOI":"10.1109\/TMC.2018.2849416","article-title":"Learning-based outdoor localization exploiting crowd-labeled WiFi hotspots","volume":"18","author":"Wang","year":"2019","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_14","first-page":"5076","article-title":"Outdoor Places of Interest Recognition with WiFi Fingerprint over Mobile Devices","volume":"2019","author":"Bisio","year":"2019","journal-title":"IEEE Int. Conf. Commun."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1974","DOI":"10.1109\/COMST.2017.2671454","article-title":"Modern WLAN Fingerprinting Indoor Positioning Methods and Deployment Challenges","volume":"19","author":"Khalajmehrabadi","year":"2017","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_16","first-page":"132","article-title":"Intelligent transport systems and effects on road traffic accidents: State of the art","volume":"2","author":"Aparicio","year":"2008","journal-title":"IET Intell. Transp. Syst."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"137","DOI":"10.3141\/2299-15","article-title":"Analysis of pedestrian travel with static bluetooth sensors","volume":"2299","author":"Malinovskiy","year":"2012","journal-title":"Transp. Res. Rec."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1109\/TWC.2011.110811.101739","article-title":"Non-line-of-sight node localization based on semi-definite programming in wireless sensor networks","volume":"11","author":"Chen","year":"2012","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1007\/s11036-010-0281-3","article-title":"Mobility-assisted node localization based on TOA measurements without time synchronization in wireless sensor networks","volume":"17","author":"Chen","year":"2012","journal-title":"Mob. Netw. Appl."},{"key":"ref_20","first-page":"956","article-title":"Mobile Element Assisted Cooperative Localization for wireless sensor networks with obstacles","volume":"9","author":"Chen","year":"2010","journal-title":"Optimization"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"8402","DOI":"10.1109\/TWC.2018.2876832","article-title":"Machine Learning Methods for RSS-Based User Positioning in Distributed Massive MIMO","volume":"17","author":"Prasad","year":"2018","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2824","DOI":"10.1109\/TVT.2017.2774103","article-title":"Signal Strength Measurements for Indoor Localization","volume":"67","author":"Yan","year":"2018","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2714","DOI":"10.1109\/TVT.2016.2584104","article-title":"Energy-Efficient Localization and Tracking of Mobile Devices in Wireless Sensor Networks","volume":"66","author":"Zheng","year":"2017","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1007\/s11036-012-0361-7","article-title":"Accurate and efficient node localization for mobile sensor networks","volume":"18","author":"Chen","year":"2013","journal-title":"Mob. Networks Appl."},{"key":"ref_25","unstructured":"(2020, April 30). WiGLE: Wireless Network Mapping. Available online: Available: https:\/\/wigle.net\/."},{"key":"ref_26","unstructured":"Radiocells.Org (2020, March 31). Home Page. Available online: Available: https:\/\/radiocells.org\/."},{"key":"ref_27","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 (Cat. No.00CH37064), Tel Aviv, Israel."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1109\/TMC.2007.1025","article-title":"Reducing the calibration effort for probabilistic indoor location estimation","volume":"6","author":"Chai","year":"2007","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"898","DOI":"10.1109\/TII.2017.2750240","article-title":"Toward Low-Overhead Fingerprint-Based Indoor Localization via Transfer Learning: Design, Implementation, and Evaluation","volume":"14","author":"Liu","year":"2018","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"10896","DOI":"10.1109\/TVT.2018.2870160","article-title":"Augmentation of Fingerprints for Indoor WiFi Localization Based on Gaussian Process Regression","volume":"67","author":"Sun","year":"2018","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1109\/TMC.2010.67","article-title":"Discriminant minimization search for large-scale RF-based localization systems","volume":"10","author":"Kuo","year":"2011","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1109\/JSEN.2018.2873357","article-title":"Kalman Filtering Framework-Based Real Time Target Tracking in Wireless Sensor Networks Using Generalized Regression Neural Networks","volume":"19","author":"Jondhale","year":"2019","journal-title":"IEEE Sens. J."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1622","DOI":"10.1109\/TIE.2011.2165462","article-title":"Toward robust indoor localization based on Bayesian filter using chirp-spread-spectrum ranging","volume":"59","author":"Wang","year":"2012","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"3619","DOI":"10.1109\/TIM.2011.2135030","article-title":"Real-time estimation of sensor node\u2019s position using particle swarm optimization with log-barrier constraint","volume":"60","author":"Nguyen","year":"2011","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"572","DOI":"10.1109\/TIE.2014.2327595","article-title":"Indoor localization based on curve fitting and location search using received signal strength","volume":"62","author":"Wang","year":"2015","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"821","DOI":"10.1109\/JSTSP.2009.2029191","article-title":"Robust indoor positioning provided by real-time rssi values in unmodified WLAN networks","volume":"3","author":"Mazuelas","year":"2009","journal-title":"IEEE J. Sel. Top. Signal Process."},{"key":"ref_37","unstructured":"Zhu, J., Luo, H., Chen, Z., and Li, Z. (2014, January 27\u201330). RSSI based Bluetooth low energy indoor positioning. Proceedings of the 2014 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Busan, Korea."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Bertuletti, S., Cereatti, A., Della, U., Caldara, M., and Galizzi, M. (2016, January 20\u201322). Indoor distance estimated from Bluetooth Low Energy signal strength: Comparison of regression models. Proceedings of the 2016 IEEE Sensors Applications Symposium (SAS), Catania, Italy.","DOI":"10.1109\/SAS.2016.7479899"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1940","DOI":"10.1109\/TIE.2018.2833021","article-title":"Dynamic wireless indoor localization incorporating with an autonomous mobile robot based on an adaptive signal model fingerprinting approach","volume":"66","author":"Luo","year":"2019","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Huang, Z., Zhu, X., Lin, Y., Xu, L., and Mao, Y. (2019, January 14\u201317). A novel WIFI-oriented RSSI signal processing method for tracking low-speed pedestrians. Proceedings of the 2019 5th International Conference on Transportation Information and Safety (ICTIS), Liverpool, UK.","DOI":"10.1109\/ICTIS.2019.8883759"},{"key":"ref_41","first-page":"55","article-title":"Research of automatically piecewise polynomial curve-fitting method based on least-square principle","volume":"14","author":"Liu","year":"2014","journal-title":"Sci. Technol. Eng."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1002\/wcm.72","article-title":"A survey of mobility models for ad hoc network research","volume":"2","author":"Camp","year":"2002","journal-title":"Wirel. Commun. Mob. Comput."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Li, G., Geng, E., Ye, Z., Xu, Y., Lin, J., and Pang, Y. (2018). Indoor positioning algorithm based on the improved RSSI distance model. Sensors, 18.","DOI":"10.3390\/s18092820"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/11\/3259\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:36:39Z","timestamp":1760175399000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/11\/3259"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,8]]},"references-count":43,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2020,6]]}},"alternative-id":["s20113259"],"URL":"https:\/\/doi.org\/10.3390\/s20113259","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,6,8]]}}}