{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:20:39Z","timestamp":1760242839195,"version":"build-2065373602"},"reference-count":26,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2016,12,15]],"date-time":"2016-12-15T00:00:00Z","timestamp":1481760000000},"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":["41271440"],"award-info":[{"award-number":["41271440"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Although map filtering-aided Pedestrian Dead Reckoning (PDR) is capable of largely improving indoor localization accuracy, it becomes less efficient when coping with highly complex indoor spaces. For instance, indoor spaces with a few close corners or neighboring passages can lead to particles entering erroneous passages, which can further cause the failure of subsequent tracking. To address this problem, we propose GridiLoc, a reliable and accurate pedestrian indoor localization method through the fusion of smartphone sensors and a grid model. The key novelty of GridiLoc is the utilization of a backtracking grid filter for improving localization accuracy and for handling dead ending issues. In order to reduce the time consumption of backtracking, a topological graph is introduced for representing candidate backtracking points, which are the expected locations at the starting time of the dead ending. Furthermore, when the dead ending is caused by the erroneous step length model of PDR, our solution can automatically calibrate the model by using the historical tracking data. Our experimental results show that GridiLoc achieves a higher localization accuracy and reliability compared with the commonly-used map filtering approach. Meanwhile, it maintains an acceptable computational complexity.<\/jats:p>","DOI":"10.3390\/s16122137","type":"journal-article","created":{"date-parts":[[2016,12,15]],"date-time":"2016-12-15T10:53:16Z","timestamp":1481799196000},"page":"2137","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["GridiLoc: A Backtracking Grid Filter for Fusing the Grid Model with PDR Using Smartphone Sensors"],"prefix":"10.3390","volume":"16","author":[{"given":"Jianga","family":"Shang","sequence":"first","affiliation":[{"name":"Faculty of Information Engineering, China University of Geosciences, Wuhan 430074, China"},{"name":"National Engineering Research Center for Geographic Information System, Wuhan 430074, China"}]},{"given":"Xuke","family":"Hu","sequence":"additional","affiliation":[{"name":"Institute of Geography, Heidelberg University, Berliner Street 48, Heidelberg D-69120, Germany"}]},{"given":"Wen","family":"Cheng","sequence":"additional","affiliation":[{"name":"Faculty of Information Engineering, China University of Geosciences, Wuhan 430074, China"},{"name":"National Engineering Research Center for Geographic Information System, Wuhan 430074, China"}]},{"given":"Hongchao","family":"Fan","sequence":"additional","affiliation":[{"name":"Institute of Geography, Heidelberg University, Berliner Street 48, Heidelberg D-69120, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2016,12,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1109\/MC.2004.1266301","article-title":"Location-aware computing comes of age","volume":"37","author":"Hazas","year":"2004","journal-title":"Computer"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Worboys, M. (2011, January 1\u20134). Modeling indoor space. Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Indoor Spatial Awareness, Chicago, IL, USA.","DOI":"10.1145\/2077357.2077358"},{"key":"ref_3","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_4","doi-asserted-by":"crossref","first-page":"1281","DOI":"10.1109\/SURV.2012.121912.00075","article-title":"A survey of indoor inertial positioning systems for pedestrians","volume":"15","author":"Harle","year":"2013","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Li, F., Zhao, C., Ding, G., Gong, J., Liu, C., and Zhao, F. (2012, January 5\u20138). A Reliable and Accurate Indoor Localization Method Using Phone Inertial Sensors. Proceedings of the 2012 ACM Conference on Ubiquitous Computing (UbiComp\u201912), Pittsburgh, PA, USA.","DOI":"10.1145\/2370216.2370280"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1304","DOI":"10.1109\/TVT.2015.2391296","article-title":"Indoor Positioning Using Efficient Map Matching, RSS Measurements, and an Improved Motion Model","volume":"64","author":"Zampella","year":"2015","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_7","unstructured":"Klepal, M., and Beauregard, S. (2008, January 27). A backtracking particle filter for fusing building plans with PDR displacement estimates. Proceedings of the 5th Workshop on Positioning, Navigation and Communication (WPNC 2008), Hannover, Germany."},{"key":"ref_8","first-page":"85","article-title":"Spatial Models for Context-Aware Indoor Navigation Systems: A Survey","volume":"1","author":"Imad","year":"2012","journal-title":"J. Spat. Inf. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1109\/MPRV.2009.90","article-title":"LOC8: A location model and extensible framework for programming with location","volume":"9","author":"Stevenson","year":"2010","journal-title":"IEEE Pervasive Comput."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1007\/s00779-004-0270-2","article-title":"On location models for ubiquitous computing","volume":"9","author":"Becker","year":"2005","journal-title":"Pers. Ubiquitous Comput."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1177\/02783640022066770","article-title":"Sensor-Based Exploration: The Hierarchical Generalized Voronoi Graph","volume":"19","author":"Choset","year":"2000","journal-title":"Int. J. Robot. Res."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1109\/MPRV.2003.1228524","article-title":"Bayesian Filtering for Location Estimation","volume":"2","author":"Fox","year":"2003","journal-title":"IEEE Pervasive Comput."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"532","DOI":"10.1016\/j.compenvurbsys.2010.07.006","article-title":"A Grid Graph-Based Model for the Analysis of 2D Indoor Spaces","volume":"34","author":"Xiang","year":"2010","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1613\/jair.616","article-title":"Markov Localization for Mobile Robots in Dynamic Environments","volume":"11","author":"Dieter","year":"1999","journal-title":"J. Artif. Intell. Res."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"4781","DOI":"10.3390\/s130404781","article-title":"On calibrating the sensor errors of a PDR-based indoor localization system","volume":"13","author":"Lan","year":"2013","journal-title":"Sensors"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Bao, H., and Wong, W.C. (2013, January 1\u20135). An Indoor Dead-Reckoning Algorithm with Map Matching. Proceedings of the 9th International Wireless Communications and Mobile Computing Conference (IWCMC), Sardinia, Italy.","DOI":"10.1109\/IWCMC.2013.6583784"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Bhattacharya, S., Flor\u00e9en, P., Forsblom, A., Myllym\u00e4ki, P., Nurmi, P., Pulkkinen, T., and Salovaara, A. (2012, January 26\u201329). Ma$$iv\u2014An Intelligent Mobile Grocery Assistant. Proceedings of the 8th International Conference on Intelligent Environments (IE), Guanajuato, Mexico.","DOI":"10.1109\/IE.2012.21"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Faragher, R.M., Sarno, C., and Newman, M. (2012, January 23\u201326). Opportunistic Radio SLAM for Indoor Navigation Using Smartphone Sensors. Proceedings of the Position Location and Navigation Symposium (PLANS), Myrtle Beach, SC, USA.","DOI":"10.1109\/PLANS.2012.6236873"},{"key":"ref_19","unstructured":"Jurgen, B., and Vogt, H. (2003). Robust Probabilistic Positioning Based on High-Level Sensor-Fusion and Map Knowledge, ETH, Swiss Federal Institute of Technology, Institute for Pervasive Computing."},{"key":"ref_20","unstructured":"Morgan, Q., Stavens, D., Coates, A., and Thrun, S. (2010, January 18\u201322). Sub-Meter Indoor Localization in Unmodified Environments with Inexpensive Sensors. Proceedings of the International Conference on Intelligent Robots and Systems (IROS), Taipei, Taiwan."},{"key":"ref_21","unstructured":"Weinberg, H. (2002). Using the ADXL202 in Pedometer and Personal Navigation Applications, Analog Devices, Inc.. Analog Devices AN-602 Application Note."},{"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","first-page":"531","DOI":"10.1080\/13658810801949850","article-title":"Finding shortest paths on real road networks: The case for A*","volume":"23","author":"Zeng","year":"2009","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Zhang, L., Tiwana, B., Qian, Z., Wang, Z., Dick, R.P., Mao, Z.M., and Yang, L. (2010, January 28). Accurate online power estimation and automatic battery behavior based power model generation for smartphones. Proceedings of the Eighth IEEE\/ACM\/IFIP International Conference on Hardware\/Software Codesign and System Synthesis, Scottsdale, AZ, USA.","DOI":"10.1145\/1878961.1878982"},{"key":"ref_25","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 (UbiComp \u201908), Seoul, Korea.","DOI":"10.1145\/1409635.1409651"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Yang, Z., Wu, C., Zhou, Z., Zhang, X., Wang, X., and Liu, Y. (2015). Mobility increases localizability: A survey on wireless indoor localization using inertial sensors. ACM Comput. Surv. CSUR, 47.","DOI":"10.1145\/2676430"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/16\/12\/2137\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:28:38Z","timestamp":1760210918000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/16\/12\/2137"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,12,15]]},"references-count":26,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2016,12]]}},"alternative-id":["s16122137"],"URL":"https:\/\/doi.org\/10.3390\/s16122137","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2016,12,15]]}}}