{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:34:39Z","timestamp":1760240079477,"version":"build-2065373602"},"reference-count":42,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2019,3,8]],"date-time":"2019-03-08T00:00:00Z","timestamp":1552003200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41804016"],"award-info":[{"award-number":["41804016"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key Research Development Program of China","award":["2016YFB0502204"],"award-info":[{"award-number":["2016YFB0502204"]}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2017M622517"],"award-info":[{"award-number":["2017M622517"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Technology Innovation Program of Hubei Province","award":["2018AAA070"],"award-info":[{"award-number":["2018AAA070"]}]},{"name":"Natural Science Fund of Hubei Province","award":["2018CFA007"],"award-info":[{"award-number":["2018CFA007"]}]},{"DOI":"10.13039\/501100011354","name":"State Key Laboratory of Geo-information Engineering","doi-asserted-by":"publisher","award":["SKLGIE2017-M-1-1"],"award-info":[{"award-number":["SKLGIE2017-M-1-1"]}],"id":[{"id":"10.13039\/501100011354","id-type":"DOI","asserted-by":"publisher"}]},{"name":"State Key Laboratory of Geodesy and Earth\u2019s Geodynamics","award":["SKLGED2018-1-4-E"],"award-info":[{"award-number":["SKLGED2018-1-4-E"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Smartphone indoor localization has attracted considerable attention over the past decade because of the considerable business potential in terms of indoor navigation and location-based services. In particular, Wi-Fi RSS (received signal strength) fingerprinting for indoor localization has received significant attention in the industry, for its advantage of freely using off-the-shelf APs (access points). However, RSS measured by heterogeneous mobile devices is generally biased due to the variety of embedded hardware, leading to a systematical mismatch between online measures and the pre-established radio maps. Additionally, the fingerprinting method based on a single RSS measurement usually suffers from signal fluctuations due to environmental changes or human body blockage, leading to possible large localization errors. In this context, this study proposes a space-constrained pairwise signal strength differences (PSSD) strategy to improve Wi-Fi fingerprinting reliability, and mitigate the effect of hardware bias of different smartphone devices on positioning accuracy without requiring a calibration process. With the efforts of these two aspects, the proposed solution enhances the usability of Wi-Fi fingerprint positioning. The PSSD approach consists of two critical operations in constructing particular fingerprints. First, we construct the signal strength difference (SSD) radio map of the area of interest, which uses the RSS differences between APs to minimize the device-dependent effect. Then, the pairwise RSS fingerprints are constructed by leveraging the time-series RSS measurements and potential spatial topology of pedestrian locations of these measurement epochs, and consequently reducing possible large positioning errors. To verify the proposed PSSD method, we carry out extensive experiments with various Android smartphones in a campus building. In the case of heterogeneous devices, the experimental results demonstrate that PSSD fingerprinting achieves a mean error \u223c20% less than conventional RSS fingerprinting. In addition, PSSD fingerprinting achieves a 90-percentile accuracy of no greater than 5.5 m across the tested heterogeneous smartphones<\/jats:p>","DOI":"10.3390\/rs11050566","type":"journal-article","created":{"date-parts":[[2019,3,8]],"date-time":"2019-03-08T11:21:59Z","timestamp":1552044119000},"page":"566","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["A Pairwise SSD Fingerprinting Method of Smartphone Indoor Localization for Enhanced Usability"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2654-6864","authenticated-orcid":false,"given":"Fan","family":"Yang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"},{"name":"State Key Laboratory of Geodesy and Earth\u2019s Geodynamics, Chinese Academy of Sciences, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian","family":"Xiong","sequence":"additional","affiliation":[{"name":"Wuhan GeoTechnical Engineering and Surveying Co. Ltd., Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingbin","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"},{"name":"Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changqing","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Geodesy and Earth\u2019s Geodynamics, Chinese Academy of Sciences, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zheng","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pengfei","family":"Tong","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6683-2342","authenticated-orcid":false,"given":"Ruizhi","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"},{"name":"Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,3,8]]},"reference":[{"key":"ref_1","unstructured":"(2017, November 23). Global Indoor Location Market Analysis (2017\u20132023). Available online: https:\/\/www.reportlinker.com\/p05207399\/Global-Indoor-Location-Market-Analysis.html."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"466","DOI":"10.1109\/COMST.2015.2464084","article-title":"Wi-Fi Fingerprint-Based Indoor Positioning: Recent Advances and Comparisons","volume":"18","author":"He","year":"2016","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_3","unstructured":"Basri, C., and Khadimi, A.E. (October, January 29). Survey on indoor localization system and recent advances of WIFI fingerprinting technique. Proceedings of the International Conference on Multimedia Computing and Systems, Marrakech, Morocco."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Correa, A., Barcelo, M., Morell, A., and Vicario, J.L. (2017). A Review of Pedestrian Indoor Positioning Systems for Mass Market Applications. Sensors, 17.","DOI":"10.3390\/s17081927"},{"key":"ref_5","unstructured":"Zafari, F., Gkelias, A., and Leung, K. (arXiv, 2017). A Survey of Indoor Localization Systems and Technologies, arXiv."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Karaagac, A., Haxhibeqiri, J., Ridolfi, M., Joseph, W., Moerman, I., and Hoebeke, J. (2017, January 12\u201315). Evaluation of accurate indoor localization systems in industrial environments. Proceedings of the IEEE International Conference on Emerging Technologies and Factory Automation, Limassol, Cyprus.","DOI":"10.1109\/ETFA.2017.8247587"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Martin, E., Vinyals, O., Friedland, G., and Bajcsy, R. (2010, January 25\u201329). Precise indoor localization using smart phones. Proceedings of the International Conference on Multimedea 2010, Firenze, Italy.","DOI":"10.1145\/1873951.1874078"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2424","DOI":"10.1109\/TIE.2015.2509917","article-title":"Gradient-Based Fingerprinting for Indoor Localization and Tracking","volume":"63","author":"Shu","year":"2016","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_9","unstructured":"Dortz, N.L., Gain, F., and Zetterberg, P. (2012, January 25\u201330). WiFi fingerprint indoor positioning system using probability distribution comparison. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, Kyoto, Japan."},{"key":"ref_10","unstructured":"Ge, X., and Qu, Z. (2016, January 26\u201328). Optimization WIFI indoor positioning KNN algorithm location-based fingerprint. Proceedings of the IEEE International Conference on Software Engineering and Service Science, Beijing, China."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Li, Z., Liu, J., Yang, F., Niu, X., Li, L., Wang, Z., and Chen, R. (2018). A Bayesian Density Model Based Radio Signal Fingerprinting Positioning Method for Enhanced Usability. Sensors, 18.","DOI":"10.3390\/s18114063"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Turner, D., Savage, S., and Snoeren, A.C. (2011, January 4\u20137). On the empirical performance of self-calibrating WiFi location systems. Proceedings of the Local Computer Networks, Bonn, Germany.","DOI":"10.1109\/LCN.2011.6115548"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1109\/TMC.2011.243","article-title":"SSD: A Robust RF Location Fingerprint Addressing Mobile Devices\u2019 Heterogeneity","volume":"12","author":"Hossain","year":"2013","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_14","unstructured":"Haeberlen, A. (October, January 26). Practical robust localization over large-scale 802.11 wireless networks. Proceedings of the International Conference on Mobile Computing and Networking, Philadelphia, PA, USA."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Kj\u00e6rgaard, M.B. (2006, January 10\u201311). Automatic mitigation of sensor variations for signal strength based location systems. Proceedings of the International Conference on Location- and Context-Awareness, Dublin, Ireland.","DOI":"10.1007\/11752967_3"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"6246","DOI":"10.1109\/TVT.2016.2630713","article-title":"Mitigating Large Errors in WiFi-based Indoor Localization for Smartphones","volume":"66","author":"Wu","year":"2017","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Kim, Y., Shin, H., and Cha, H. (2012, January 19\u201323). Smartphone-based Wi-Fi pedestrian-tracking system tolerating the RSS variance problem. Proceedings of the IEEE International Conference on Pervasive Computing and Communications, Lugano, Switzerland.","DOI":"10.1109\/PerCom.2012.6199844"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"715","DOI":"10.3390\/s150100715","article-title":"Fusion of WiFi, smartphone sensors and landmarks using the Kalman filter for indoor localization","volume":"15","author":"Chen","year":"2015","journal-title":"Sensors"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"17208","DOI":"10.3390\/s121217208","article-title":"A Hybrid Smartphone Indoor Positioning Solution for Mobile LBS","volume":"12","author":"Liu","year":"2012","journal-title":"Sensors"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"677","DOI":"10.1007\/s11036-008-0139-0","article-title":"Unsupervised Learning for Solving RSS Hardware Variance Problem in WiFi Localization","volume":"14","author":"Tsui","year":"2009","journal-title":"Mob. Netw. Appl."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Han, S., Zhao, C., Meng, W., and Li, C. (2015, January 8\u201312). Cosine similarity based fingerprinting algorithm in WLAN indoor positioning against device diversity. Proceedings of the IEEE International Conference on Communications, London, UK.","DOI":"10.1109\/ICC.2015.7248735"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1109\/LSP.2016.2519607","article-title":"An Improved K-Nearest-Neighbor Indoor Localization Method Based on Spearman Distance","volume":"23","author":"Xie","year":"2016","journal-title":"IEEE Signal Process. Lett."},{"key":"ref_23","unstructured":"Wang, L., Wu, X., Zheng, B., Cui, J., and Zhou, H. (2017, January 7\u20139). A cosine similarity-based compensation strategy for RSS detection variance in indoor localization. Proceedings of the Telecommunication Networks and Applications Conference, Dunedin, New Zealand."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Dong, F., Chen, Y., Liu, J., Ning, Q., and Piao, S. (2009, January 30). A Calibration-Free Localization Solution for Handling Signal Strength Variance. Proceedings of the International Conference on Mobile Entity Localization and Tracking in GPS-Less Environments, Orlando, FL, USA.","DOI":"10.1007\/978-3-642-04385-7_6"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1080\/17489725.2013.816792","article-title":"Device self-calibration in location systems using signal strength histograms","volume":"7","author":"Laoudias","year":"2013","journal-title":"J. Locat. Based Serv."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1109\/TVT.2005.863405","article-title":"Analysis of hyperbolic and circular positioning algorithms using stationary signal-strength-difference measurements in wireless communications","volume":"55","author":"Liu","year":"2006","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Kjrgaard, M.B., and Munk, C.V. (2008, January 17\u201321). Hyperbolic Location Fingerprinting: A Calibration-Free Solution for Handling Differences in Signal Strength (concise contribution). Proceedings of the IEEE International Conference on Pervasive Computing and Communications, Hong Kong, China.","DOI":"10.1109\/PERCOM.2008.75"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"573582","DOI":"10.1155\/2015\/573582","article-title":"Weight-RSS: A calibration-free and robust method for WLAN-Based indoor positioning","volume":"11","author":"Zheng","year":"2015","journal-title":"Int. J. Distrib. Sens. Netw."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Fang, S.H., Wang, C.H., Chiou, S.M., and Lin, P. (2012, January 6\u20139). Calibration-Free Approaches for Robust Wi-Fi Positioning against Device Diversity: A Performance Comparison. Proceedings of the Vehicular Technology Conference, Yokohama, Japan.","DOI":"10.1109\/VETECS.2012.6240088"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Fet, N., Handte, M., and Marr\u00f3n, P.J. (2013, January 8\u201312). A model for WLAN signal attenuation of the human body. Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing, Zurich, Switzerland.","DOI":"10.1145\/2493432.2493459"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Li, X., Wang, J., Liu, C., Zhang, L., and Li, Z. (2016). Integrated WiFi\/PDR\/Smartphone Using an Adaptive System Noise Extended Kalman Filter Algorithm for Indoor Localization. ISPRS Int. J. Geo-Inf., 5.","DOI":"10.3390\/ijgi5020008"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"24595","DOI":"10.3390\/s150924595","article-title":"Integrated WiFi\/PDR\/Smartphone Using an Unscented Kalman Filter Algorithm for 3D Indoor Localization","volume":"15","author":"Chen","year":"2015","journal-title":"Sensors"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1016\/j.aeue.2015.12.004","article-title":"RSS-based indoor localization with PDR location tracking for wireless sensor networks","volume":"70","author":"Cho","year":"2016","journal-title":"AEUE Int. J. Electron. Commun."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Zhang, M., Shen, W., Yao, Z., and Zhu, J. (2016, January 27\u201329). Multiple information fusion indoor location algorithm based on WIFI and improved PDR. Proceedings of the Chinese Control Conference, Chengdu, China.","DOI":"10.1109\/ChiCC.2016.7554144"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Koo, B., Lee, S., Lee, M., Lee, D., Lee, S., and Kim, S. (2014, January 27\u201330). PDR\/fingerprinting fusion indoor location tracking using RSS recovery and clustering. Proceedings of the International Conference on Indoor Positioning and Indoor Navigation, Busan, South Korea.","DOI":"10.1109\/IPIN.2014.7275546"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Hassan, M. (2012, January 12\u201314). A performance model of pedestrian dead reckoning with activity-based location updates. Proceedings of the IEEE International Conference on Networks, Singapore.","DOI":"10.1109\/ICON.2012.6506535"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Radu, V., and Marina, M.K. (2013, January 28\u201331). HiMLoc: Indoor smartphone localization via activity aware Pedestrian Dead Reckoning with selective crowdsourced WiFi fingerprinting. Proceedings of the International Conference on Indoor Positioning and Indoor Navigation, FMontbeliard-Belfort, France.","DOI":"10.1109\/IPIN.2013.6817916"},{"key":"ref_38","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 INFOCOM 2000, Nineteenth Joint Conference of the IEEE Computer and Communications Societies, Tel Aviv, Israel."},{"key":"ref_39","unstructured":"Rappaport, T.S. (1995). Wireless Communications: Principles and Practice, Prentice-Hall, Inc."},{"key":"ref_40","unstructured":"Saunders, S.R., and Simon, S.R. (1999). Antennas and Propagation for Wireless Communication Systems, J. Wiley and Sons, Inc."},{"key":"ref_41","first-page":"36","article-title":"Frequency and velocity of people walking","volume":"84","author":"Aitaterini","year":"2005","journal-title":"Struct. Eng."},{"key":"ref_42","unstructured":"International Association of Geodesy, Symposia, and Brunner, F.K. (1998). WGS 84\u2014Past, Present and Future. Advances in Positioning and Reference Frames, Springer."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/5\/566\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:37:19Z","timestamp":1760186239000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/5\/566"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,3,8]]},"references-count":42,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2019,3]]}},"alternative-id":["rs11050566"],"URL":"https:\/\/doi.org\/10.3390\/rs11050566","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2019,3,8]]}}}