{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T14:34:05Z","timestamp":1774449245677,"version":"3.50.1"},"reference-count":29,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2020,11,23]],"date-time":"2020-11-23T00:00:00Z","timestamp":1606089600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The National Key Research and Development Program of China","award":["(No.2016YFB0502204)"],"award-info":[{"award-number":["(No.2016YFB0502204)"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Map-matching is a popular method that uses spatial information to improve the accuracy of positioning methods. The performance of map matching methods is closely related to spatial characteristics. Although several studies have demonstrated that certain map matching algorithms are affected by some spatial structures (e.g., parallel paths), they focus on the analysis of single map matching method or few spatial structures. In this study, we explored how the most commonly-used four spatial characteristics (namely forks, open spaces, corners, and narrow corridors) affect three popular map matching methods, namely particle filtering (PF), hidden Markov model (HMM), and geometric methods. We first provide a theoretical analysis on how spatial characteristics affect the performance of map matching methods, and then evaluate these effects through experiments. We found that corners and narrow corridors are helpful in improving the positioning accuracy, while forks and open spaces often lead to a larger positioning error. We hope that our findings are helpful for future researchers in choosing proper map matching algorithms with considering the spatial characteristics.<\/jats:p>","DOI":"10.3390\/s20226698","type":"journal-article","created":{"date-parts":[[2020,11,23]],"date-time":"2020-11-23T08:18:23Z","timestamp":1606119503000},"page":"6698","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Effect Evaluation of Spatial Characteristics on Map Matching-Based Indoor Positioning"],"prefix":"10.3390","volume":"20","author":[{"given":"Shuaiwei","family":"Luo","sequence":"first","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences, Wuhan 430078, China"},{"name":"College of Tourism and Planning, Pingdingshan University, Pingdingshan 467000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3408-982X","authenticated-orcid":false,"given":"Fuqiang","family":"Gu","sequence":"additional","affiliation":[{"name":"School of Computing, National University of Singapore, Singapore 117418, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fan","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences, Wuhan 430078, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianga","family":"Shang","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences, Wuhan 430078, China"},{"name":"National Engineering Research Center for Geographic Information System, Wuhan 430078, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"397298","DOI":"10.1155\/2015\/397298","article-title":"Improvement schemes for indoor mobile location estimation: A survey","volume":"2015","author":"Shang","year":"2015","journal-title":"Math. Probl. Eng."},{"key":"ref_2","first-page":"4041291","article-title":"A survey of crowd sensing opportunistic signals for indoor localization","volume":"2016","author":"Pei","year":"2016","journal-title":"Mob. Inf. Syst."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Li, Y., Zhuang, Y., Hu, X., Gao, Z., Hu, J., Chen, L., He, Z., Pei, L., Chen, K., and Wang, M. (2020). Location-Enabled IoT (LE-IoT): A Survey of Positioning Techniques, Error Sources, and Mitigation. arXiv.","DOI":"10.1109\/JIOT.2020.3019199"},{"key":"ref_4","unstructured":"Li, Y., Zhuang, Y., Hu, X., Gao, Z., Hu, J., Chen, L., He, Z., Pei, L., Chen, K., and Wang, M. (2020, November 23). Toward Location-Enabled IoT (LE-IoT): IoT Positioning Techniques, Error Sources, and Error Mitigation. Available online: https:\/\/ieeexplore.ieee.org\/document\/9184896\/metrics#metrics."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Sim\u00f5es, W.C., Machado, G.S., Sales, A., de Lucena, M.M., Jazdi, N., and de Lucena, V.F. (2020). A Review of Technologies and Techniques for Indoor Navigation Systems for the Visually Impaired. Sensors, 20.","DOI":"10.3390\/s20143935"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1963","DOI":"10.1109\/COMST.2018.2806558","article-title":"A survey of positioning systems using visible LED lights","volume":"20","author":"Zhuang","year":"2018","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Yu, C., Lan, H., Gu, F., Yu, F., and El-Sheimy, N. (2017). A map\/INS\/Wi-Fi integrated system for indoor location-based service applications. Sensors, 17.","DOI":"10.3390\/s17061272"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"793","DOI":"10.3390\/mi6060793","article-title":"PDR\/INS\/WiFi integration based on handheld devices for indoor pedestrian navigation","volume":"6","author":"Zhuang","year":"2015","journal-title":"Micromachines"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3585","DOI":"10.1109\/JIOT.2018.2889303","article-title":"Toward robust crowdsourcing-based localization: A fingerprinting accuracy indicator enhanced wireless\/magnetic\/inertial integration approach","volume":"6","author":"Li","year":"2018","journal-title":"IEEE Internet Things J."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Yu, Y., Chen, R., Chen, L., Xu, S., Li, W., Wu, Y., and Zhou, H. (2020, November 23). Precise 3D Indoor Localization Based on Wi-Fi FTM and Built-in Sensors. Available online: https:\/\/ieeexplore.ieee.org\/document\/9107223.","DOI":"10.1109\/JIOT.2020.2999626"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"371","DOI":"10.5194\/isprs-annals-IV-2-W4-371-2017","article-title":"Indoor positioning by visual-inertial odometry","volume":"4","author":"Ramezani","year":"2017","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Zhang, J., Ren, M., Wang, P., Meng, J., and Mu, Y. (2020). Indoor Localization Based on VIO System and Three-Dimensional Map Matching. Sensors, 20.","DOI":"10.3390\/s20102790"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"3100","DOI":"10.1109\/JSEN.2019.2891313","article-title":"HTrack:: An Efficient Heading-Aided Map Matching for Indoor Localization and Tracking","volume":"19","author":"Wu","year":"2019","journal-title":"IEEE Sens. J."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1109\/TIM.2018.2863478","article-title":"Indoor localization on smartphones using built-in sensors and map constraints","volume":"68","author":"Xia","year":"2018","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"6477","DOI":"10.1109\/JSEN.2019.2909195","article-title":"Magnetic-based indoor localization using smartphone via a fusion algorithm","volume":"19","author":"Wang","year":"2019","journal-title":"IEEE Sens. J."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3322241","article-title":"Indoor localization improved by spatial context-A survey","volume":"52","author":"Gu","year":"2019","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/S0968-090X(00)00026-7","article-title":"Some map matching algorithms for personal navigation assistants","volume":"8","author":"White","year":"2000","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Ma, L., Fan, Y., Xu, Y., and Cui, Y. (2017, January 21\u201325). Pedestrian dead reckoning trajectory matching method for radio map crowdsourcing building in WiFi indoor positioning system. Proceedings of the 2017 IEEE International Conference on Communications (ICC), Paris, France.","DOI":"10.1109\/ICC.2017.7996457"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Abdelbar, M., and Buehrer, R.M. (2016, January 11\u201314). Improving cellular positioning indoors through trajectory matching. Proceedings of the Position, Location and Navigation Symposium (PLANS), 2016 IEEE\/ION, Savannah, GA, USA.","DOI":"10.1109\/PLANS.2016.7479705"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Xiao, Z., Wen, H., Markham, A., and Trigoni, N. (2014, January 15\u201317). Lightweight map matching for indoor localisation using conditional random fields. Proceedings of the IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks, Berlin, Germany.","DOI":"10.1109\/IPSN.2014.6846747"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Woodman, O., and Harle, R. (2008, January 21\u201324). Pedestrian localisation for indoor environments. Proceedings of the 10th International Conference on Ubiquitous Computing, Seoul, Korea.","DOI":"10.1145\/1409635.1409651"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"27251","DOI":"10.3390\/s151027251","article-title":"Apfiloc: An infrastructure-free indoor localization method fusing smartphone inertial sensors, landmarks and map information","volume":"15","author":"Shang","year":"2015","journal-title":"Sensors"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Hilsenbeck, S., Bobkov, D., Schroth, G., Huitl, R., and Steinbach, E. (2014, January 13\u201317). Graph-based data fusion of pedometer and WiFi measurements for mobile indoor positioning. Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Washington, DC, USA.","DOI":"10.1145\/2632048.2636079"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"562","DOI":"10.1109\/THMS.2014.2368092","article-title":"Activity sequence-based indoor pedestrian localization using smartphones","volume":"45","author":"Zhou","year":"2014","journal-title":"IEEE Trans. Hum. Mach. Syst."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1347","DOI":"10.1109\/COMST.2016.2637663","article-title":"A survey of selected indoor positioning methods for smartphones","volume":"19","author":"Davidson","year":"2016","journal-title":"IEEE Commun. Surv. Tutorials"},{"key":"ref_26","unstructured":"Ilkovi\u010dov\u00e1, L., Kaj\u00e1nek, P., and Kop\u00e1\u010dik, A. (2016, January 20\u201322). Pedestrian indoor positioning and tracking using smartphone sensors step detection and map matching algorithm. Proceedings of the International Symposium on Engineering Geodesy, Vara\u017edin, Croatia."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"8343","DOI":"10.1109\/JIOT.2020.2989501","article-title":"Landmark Graph-based Indoor Localization","volume":"4","author":"Gu","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"04014113","DOI":"10.1061\/(ASCE)CP.1943-5487.0000439","article-title":"Effects of positioning data quality and navigation models on map-matching of indoor positioning data","volume":"30","author":"Taneja","year":"2016","journal-title":"J. Comput. Civ. Eng."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Meng, J., Ren, M., Wang, P., Zhang, J., and Mou, Y. (2020). Improving Positioning Accuracy via Map Matching Algorithm for Visual\u2014Inertial Odometer. Sensors, 20.","DOI":"10.3390\/s20020552"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/22\/6698\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:36:05Z","timestamp":1760178965000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/22\/6698"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,23]]},"references-count":29,"journal-issue":{"issue":"22","published-online":{"date-parts":[[2020,11]]}},"alternative-id":["s20226698"],"URL":"https:\/\/doi.org\/10.3390\/s20226698","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,11,23]]}}}