{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T06:04:04Z","timestamp":1760853844049,"version":"build-2065373602"},"reference-count":24,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2015,9,8]],"date-time":"2015-09-08T00:00:00Z","timestamp":1441670400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003141","name":"Consejo Nacional de Ciencia y Tecnolog\u00eda","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003141","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Signal strength-based positioning in wireless sensor networks is a key technology for seamless, ubiquitous localization, especially in areas where Global Navigation Satellite System (GNSS) signals propagate poorly. To enable wireless local area network (WLAN) location fingerprinting in larger areas while maintaining accuracy, methods to reduce the effort of radio map creation must be consolidated and automatized. Gaussian process regression has been applied to overcome this issue, also with auspicious results, but the fit of the model was never thoroughly assessed. Instead, most studies trained a readily available model, relying on the zero mean and squared exponential covariance function, without further scrutinization. This paper studies the Gaussian process regression model selection for WLAN fingerprinting in indoor and outdoor environments. We train several models for indoor\/outdoor- and combined areas; we evaluate them quantitatively and compare them by means of adequate model measures, hence assessing the fit of these models directly. To illuminate the quality of the model fit, the residuals of the proposed model are investigated, as well. Comparative experiments on the positioning performance verify and conclude the model selection. In this way, we show that the standard model is not the most appropriate, discuss alternatives and present our best candidate.<\/jats:p>","DOI":"10.3390\/s150922587","type":"journal-article","created":{"date-parts":[[2015,9,8]],"date-time":"2015-09-08T11:59:54Z","timestamp":1441713594000},"page":"22587-22615","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["Revisiting Gaussian Process Regression Modeling for Localization in Wireless Sensor Networks"],"prefix":"10.3390","volume":"15","author":[{"given":"Philipp","family":"Richter","sequence":"first","affiliation":[{"name":"Facultad de Ingenier\u00eda, Universidad Aut\u00f3noma de Quer\u00e9taro, Cerro de las Campanas s\/n., Col. Las Campanas, Santiago de Quer\u00e9taro 76010, Mexico"}]},{"given":"Manuel","family":"Toledano-Ayala","sequence":"additional","affiliation":[{"name":"Facultad de Ingenier\u00eda, Universidad Aut\u00f3noma de Quer\u00e9taro, Cerro de las Campanas s\/n., Col. Las Campanas, Santiago de Quer\u00e9taro 76010, Mexico"}]}],"member":"1968","published-online":{"date-parts":[[2015,9,8]]},"reference":[{"key":"ref_1","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_2","doi-asserted-by":"crossref","first-page":"8358","DOI":"10.3390\/s150408358","article-title":"A Novel Method for Constructing a WIFI Positioning System with Efficient Manpower","volume":"15","author":"Du","year":"2015","journal-title":"Sensors"},{"key":"ref_3","unstructured":"Elnahrawy, E., Li, X., and Martin, R.P. (2004, January 4\u20137). The limits of localization using signal strength: A comparative study. Proceedings of the First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (IEEE SECON 2004), Santa Clara, CA, USA."},{"key":"ref_4","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_5","unstructured":"Howard, A., Siddiqi, S., and Sukhatme, G.S. (2003, January 14\u201316). An Experimental Study of Localization Using Wireless Ethernet. Proceedings of the International Conference on Field and Service Robotics, Yamanashi, Japan."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Ferris, B., H\u00e4hnel, D., and Fox, D. (2006, January 16\u201319). Gaussian processes for signal strength-based location estimation. Proceedings of Robotics: Science and Systems II, Philadelphia, PA, USA.","DOI":"10.15607\/RSS.2006.II.039"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Duvallet, F., and Tews, A.D. (2008, January 22\u201326). WiFi position estimation in industrial environments using Gaussian processes. Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS 2008), Nice, France.","DOI":"10.1109\/IROS.2008.4650910"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1774","DOI":"10.1109\/TMC.2012.143","article-title":"Dynamic Online-Calibrated Radio Maps for Indoor Positioning in Wireless Local Area Networks","volume":"12","author":"Atia","year":"2013","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"23871","DOI":"10.3390\/s141223871","article-title":"Target Tracking and Classification from Labeled and Unlabeled Data in Wireless Sensor Networks","volume":"14","author":"Yoo","year":"2014","journal-title":"Sensors"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1341","DOI":"10.1109\/TRO.2008.2004887","article-title":"Gaussian Process Models for Indoor and Outdoor Sensor-Centric Robot Localization","volume":"24","author":"Brooks","year":"2008","journal-title":"IEEE Trans. Robot."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.imavis.2015.04.002","article-title":"Feature selection for position estimation using an omnidirectional camera","volume":"39","author":"Do","year":"2015","journal-title":"Image Vis. Comput."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Bekkali, A., Masuo, T., Tominaga, T., Nakamoto, N., and Ban, H. (2011, January 14\u201316). Gaussian processes for learning-based indoor localization. Proceedings of the IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), Xi\u2019an, China.","DOI":"10.1109\/ICSPCC.2011.6061737"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1376","DOI":"10.1109\/TVT.2015.2397446","article-title":"X-ray Vision with Only WiFi Power Measurements Using Rytov Wave Models","volume":"64","author":"Depatla","year":"2015","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Rasmussen, C.E., and Williams, C.K.I. (2006). Gaussian Processes for Machine Learning, MIT Press.","DOI":"10.7551\/mitpress\/3206.001.0001"},{"key":"ref_15","unstructured":"Rappaport, T.S. (2001). Wireless Communications: Principles and Practice, Prentice Hall PTR. [2 ed.]."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"292","DOI":"10.1016\/j.pmcj.2011.09.003","article-title":"Analysis of WLAN\u2019s received signal strength indication for indoor location fingerprinting","volume":"8","author":"Kaemarungsi","year":"2012","journal-title":"Pervasive Mob. Comput."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Mirowski, P., Steck, H., Whiting, P., Palaniappan, R., MacDonald, M., and Ho, T.K. (2011, January 21\u201323). KL-divergence kernel regression for non-Gaussian fingerprint based localization. Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN), Guimar\u00e3es, Portugal.","DOI":"10.1109\/IPIN.2011.6071928"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1145\/1317425.1317431","article-title":"An Algorithm for Fast, Model-free Tracking Indoors","volume":"11","author":"Chen","year":"2007","journal-title":"SIGMOBILE Mob. Comput. Commun. Rev."},{"key":"ref_19","unstructured":"Youssef, M., Agrawala, A., and Shankar, U. (2003, January 26\u201326). WLAN Location Determination via Clustering and Probability Distributions. Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003 (PerCom 2003), Fort Worth, TX, USA."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1080\/17489725.2012.694723","article-title":"Probability kernel regression for WiFi localisation","volume":"6","author":"Mirowski","year":"2012","journal-title":"J. Locat. Based Serv."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1023\/A:1016003126882","article-title":"A Probabilistic Approach to WLAN User Location Estimation","volume":"9","author":"Roos","year":"2002","journal-title":"Int. J. Wirel. Inf. Netw."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Honkavirta, V., Per\u00e4l\u00e4, T., Ali-L\u00f6ytty, S., and Pich\u00e9, R. (2009, January 19). A Comparative Survey of WLAN Location Fingerprinting Methods. Proceedings of the 6th Workshop on Positioning, Navigation and Communication 2009 (WPNC\u201909), Hannover, Germany.","DOI":"10.1109\/WPNC.2009.4907834"},{"key":"ref_23","unstructured":"Duvenaud, D., Nickisch, H., and Rasmussen, C.E. Additive Gaussian Processes. Available online: http:\/\/papers.nips.cc\/paper\/4221-additive-gaussian-processes."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Lloyd, J.R., Duvenaud, D., Grosse, R., Tenenbaum, J.B., and Ghahramani, Z. (2014). Automatic Construction and Natural-Language Description of Nonparametric Regression Models. ArXiv E-Prints.","DOI":"10.1609\/aaai.v28i1.8904"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/15\/9\/22587\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:48:07Z","timestamp":1760215687000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/15\/9\/22587"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,9,8]]},"references-count":24,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2015,9]]}},"alternative-id":["s150922587"],"URL":"https:\/\/doi.org\/10.3390\/s150922587","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2015,9,8]]}}}