{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:26:26Z","timestamp":1760243186989,"version":"build-2065373602"},"reference-count":37,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2014,1,22]],"date-time":"2014-01-22T00:00:00Z","timestamp":1390348800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Indoor positioning systems based on the fingerprint method are widely used due to the large number of existing devices with a wide range of coverage. However, extensive positioning regions with a massive fingerprint database may cause high computational complexity and error margins, therefore clustering methods are widely applied as a solution. However, traditional clustering methods in positioning systems can only measure the similarity of the Received Signal Strength without being concerned with the continuity of physical coordinates. Besides, outage of access points could result in asymmetric matching problems which severely affect the fine positioning procedure. To solve these issues, in this paper we propose a positioning system based on the Spatial Division Clustering (SDC) method for clustering the fingerprint dataset subject to physical distance constraints. With the Genetic Algorithm and Support Vector Machine techniques, SDC can achieve higher coarse positioning accuracy than traditional clustering algorithms. In terms of fine localization, based on the Kernel Principal Component Analysis method, the proposed positioning system outperforms its counterparts based on other feature extraction methods in low dimensionality. Apart from balancing online matching computational burden, the new positioning system exhibits advantageous performance on radio map clustering, and also shows better robustness and adaptability in the asymmetric matching problem aspect.<\/jats:p>","DOI":"10.3390\/s140101850","type":"journal-article","created":{"date-parts":[[2014,1,22]],"date-time":"2014-01-22T12:32:23Z","timestamp":1390393943000},"page":"1850-1876","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["A Spatial Division Clustering Method and Low Dimensional Feature Extraction Technique Based Indoor Positioning System"],"prefix":"10.3390","volume":"14","author":[{"given":"Yun","family":"Mo","sequence":"first","affiliation":[{"name":"Communication Research Center, School of Electronics Information Engineering,  Harbin Institute of Technology, Harbin 150001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhongzhao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Communication Research Center, School of Electronics Information Engineering,  Harbin Institute of Technology, Harbin 150001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weixiao","family":"Meng","sequence":"additional","affiliation":[{"name":"Communication Research Center, School of Electronics Information Engineering,  Harbin Institute of Technology, Harbin 150001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lin","family":"Ma","sequence":"additional","affiliation":[{"name":"Communication Research Center, School of Electronics Information Engineering,  Harbin Institute of Technology, Harbin 150001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yao","family":"Wang","sequence":"additional","affiliation":[{"name":"Communication Research Center, School of Electronics Information Engineering,  Harbin Institute of Technology, Harbin 150001, China"},{"name":"Communication Department, Shenyang Artillery Academy, Shenyang 110867, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2014,1,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1807","DOI":"10.1016\/j.jnca.2012.07.005","article-title":"Kernel-based particle filtering for indoor tracking in WLANs","volume":"35","author":"Zhang","year":"2012","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Latif, S., Tariq, R., Haq, W., and Hashmi, U. (2012, January 9\u201312). Indoor Positioning System Using Ultrasonics. Islamabad, Pakistan.","DOI":"10.1109\/IBCAST.2012.6177596"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Wirola, L., Laine, T.A., and Syrjarinne, J. (2010, January 15\u201317). Mass-Market Requirements for Indoor Positioning and Indoor Navigation. Zurich, Switzerland.","DOI":"10.1109\/IPIN.2010.5646748"},{"key":"ref_4","unstructured":"Kaemarungsi, K., and Krishnamurthy, P. (2004, January 7\u201311). Modeling of Indoor Positioning Systems Based on Location Fingerprinting."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2430","DOI":"10.3390\/s130202430","article-title":"Fusion of building information and range imaging for autonomous location estimation in indoor environments","volume":"13","author":"Kohoutek","year":"2013","journal-title":"Sensors"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"8236","DOI":"10.3390\/s120608236","article-title":"An indoor navigation system for the visually impaired","volume":"12","author":"Guerrero","year":"2012","journal-title":"Sensors"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Yucel, H., Ozkir, T., Edizkan, R., and Yazici, A. (2012, January 2\u20134). Development of Indoor Positioning System with Ultrasonic and Infrared Signals. Trabzon, Turkey.","DOI":"10.1109\/INISTA.2012.6246983"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Raitoharju, M., Fadjukoff, T., Ali-Loytty, S., and Piche, R. (2012, January 23\u201326). Using Unlocated Fingerprints in Generation of WLAN Maps for Indoor Positioning. Myrtle Beach, SC, USA.","DOI":"10.1109\/PLANS.2012.6236930"},{"key":"ref_9","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_10","unstructured":"Liu, X., Zhang, S., Zhao, Q., and Lin, X. (2010, January 18\u201320). A Real-Time Algorithm for Fingerprint Localization Based on Clustering and Spatial Diversity. Moscow, Russia."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"877","DOI":"10.1109\/TKDE.2006.112","article-title":"Power-efficient access-point selection for indoor location estimation","volume":"18","author":"Chen","year":"2006","journal-title":"IEEE Tran. Knowl. Data Eng."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1983","DOI":"10.1109\/TMC.2011.216","article-title":"Received-signal-strength-based indoor positioning using compressive sensing","volume":"11","author":"Feng","year":"2012","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"676","DOI":"10.1109\/TPDS.2011.213","article-title":"Fingerprinting mobile user positions in sensor networks: Attacks and countermeasures","volume":"23","author":"Li","year":"2012","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"738","DOI":"10.1016\/j.comcom.2011.12.011","article-title":"Indoor positioning via nonlinear discriminative feature extraction in wireless local area network","volume":"35","author":"Deng","year":"2012","journal-title":"Comput. Commun."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Xu, Y.B., Deng, Z.A., and Meng, W.X. (2010, January 6\u201310). An Indoor Positioning Algorithm with Kernel Direct Discriminant Analysis. Miami, FL, USA.","DOI":"10.1109\/GLOCOM.2010.5684295"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1973","DOI":"10.1109\/TNN.2008.2005494","article-title":"Indoor location system based on discriminant-adaptive neural network in IEEE 802.11 environments","volume":"19","author":"Fang","year":"2008","journal-title":"IEEE Trans. Neural Netw."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1109\/TMC.2011.30","article-title":"Principal component localization in indoor WLAN environments","volume":"11","author":"Fang","year":"2012","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1037","DOI":"10.1109\/TVT.2011.2107757","article-title":"A dynamic hybrid projection approach for improved Wi-Fi location fingerprinting","volume":"60","author":"Fang","year":"2011","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2319","DOI":"10.1126\/science.290.5500.2319","article-title":"A global geometric framework for nonlinear dimensionality reduction","volume":"290","author":"Tenenbaum","year":"2000","journal-title":"Science"},{"key":"ref_20","first-page":"794","article-title":"Joint AP selection and local discriminant embedding for energy efficient and accurate Wi-Fi positioning","volume":"6","author":"Deng","year":"2012","journal-title":"KSII Trans. Internet Informa. Syst."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Vapnik, V.N. (1999). The Nature of Statistical Learning Theory, Springer. [2nd ed.].","DOI":"10.1007\/978-1-4757-3264-1"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"15292","DOI":"10.3390\/s121115292","article-title":"A modular spectrum sensing system based on PSO-SVM","volume":"12","author":"Cai","year":"2012","journal-title":"Sensors"},{"key":"ref_23","unstructured":"Sivanandam, S.N., and Deepa, S.N. (2007). Introduction to Genetic Algorithms, Springer. [1st ed.]."},{"key":"ref_24","unstructured":"Theodoridis, S., and Koutroumbas, K. (2005). Pattern Recognition, Academic Press. [3rd ed.]."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"572","DOI":"10.1109\/TPAMI.2004.1273927","article-title":"Gabor-based kernel PCA with fractional power polynomial models for face recognition","volume":"26","author":"Liu","year":"2004","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Ham, J., Lee, D.D., Mika, S., and Scholkopf, B. (2004, January 4\u20138). A Kernel View of the Dimensionality Reduction of Manifolds. Banff, AB, Canada.","DOI":"10.1145\/1015330.1015417"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1109\/TNN.2007.904040","article-title":"Pruning noisy bases in discriminant analysis","volume":"19","author":"Zhu","year":"2008","journal-title":"IEEE Trans. Neural Netw."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1002\/dac.746","article-title":"Linear discriminant analysis in network traffic modeling","volume":"19","author":"Zhang","year":"2006","journal-title":"Int. J Commun. Syst."},{"key":"ref_29","unstructured":"Chen, H.T., Chang, H.W., and Liu, T.L. (2005, January 20\u201325). Local Discriminant Embedding and Its Variants. San Diego, CA, USA."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1049\/iet-cvi.2011.0028","article-title":"Feature extraction based on fuzzy local discriminant embedding with applications to face recognition","volume":"5","author":"Wan","year":"2011","journal-title":"IET Comput. Vis."},{"key":"ref_31","unstructured":"(2005). IEEE Amendment to IEEE Std 802.11, IEEE Computer Society."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1109\/TMC.2011.243","article-title":"SSD: A robust RF location fingerprint addressing mobile devices' heterogeneity","volume":"12","author":"Hossain","year":"2013","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"11085","DOI":"10.3390\/s130811085","article-title":"An improved algorithm to generate a Wi-Fi fingerprint database for indoor positioning","volume":"13","author":"Chen","year":"2013","journal-title":"Sensors"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"689","DOI":"10.1109\/TMC.2007.1017","article-title":"Kernel-based positioning in wireless local area networks","volume":"13","author":"Kushki","year":"2007","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_35","unstructured":"Castro, P., Chiu, P., Kremenek, T., and Muntz, R.R. (October, January 30). A Probabilistic Room Location Service for Wireless Networked Environments. Atlanta, GA, USA."},{"key":"ref_36","unstructured":"Xu, Y., Yang, J.Y., and Lu, J.F. (2005, January 18\u201321). An Efficient Kernel-Based Nonlinear Regression Method for Two-Class Classification. Guangzhou, China."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1026","DOI":"10.1016\/j.patcog.2005.10.029","article-title":"A fast kernel-based nonlinear discriminant analysis for multi-class classification","volume":"39","author":"Xu","year":"2006","journal-title":"Pattern Recogn."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/14\/1\/1850\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:07:35Z","timestamp":1760216855000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/14\/1\/1850"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,1,22]]},"references-count":37,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2014,1]]}},"alternative-id":["s140101850"],"URL":"https:\/\/doi.org\/10.3390\/s140101850","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2014,1,22]]}}}