{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,7,27]],"date-time":"2023-07-27T16:25:23Z","timestamp":1690475123919},"reference-count":38,"publisher":"SAGE Publications","issue":"8","license":[{"start":{"date-parts":[[2017,8,1]],"date-time":"2017-08-01T00:00:00Z","timestamp":1501545600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Distributed Sensor Networks"],"published-print":{"date-parts":[[2017,8]]},"abstract":"<jats:p> Due to the vast increase in location-based services, currently there exists an actual need of robust and reliable indoor localization solutions. Received signal strength localization is widely used due to its simplicity and availability in most mobile devices. The received signal strength channel model is defined by the propagation losses and the shadow fading. In real-life applications, these parameters might vary over time because of changes in the environment. Thus, to obtain a reliable localization solution, they have to be sequentially estimated. In this article, the problem of tracking a mobile node by received signal strength measurements is addressed, simultaneously estimating the model parameters. Particularly, a two-slope path loss model is assumed for the received signal strength observations, which provides a more realistic representation of the propagation channel. The proposed methodology considers a parallel interacting multiple model\u2013based architecture for distance estimation, which is coupled with the on-line estimation of the model parameters and the final position determination via Kalman filtering. Numerical simulation results in realistic scenarios are provided to support the theoretical discussion and to show the enhanced performance of the new robust indoor localization approach. Additionally, experimental results using real data are reported to validate the technique. <\/jats:p>","DOI":"10.1177\/1550147717722158","type":"journal-article","created":{"date-parts":[[2017,8,29]],"date-time":"2017-08-29T07:32:20Z","timestamp":1503991940000},"page":"155014771772215","update-policy":"http:\/\/dx.doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":9,"title":["Received signal strength\u2013based indoor localization using a robust interacting multiple model\u2013extended Kalman filter algorithm"],"prefix":"10.1177","volume":"13","author":[{"given":"Juan Manuel","family":"Castro-Arvizu","sequence":"first","affiliation":[{"name":"Universitat Polit\u00e8cnica de Catalunya (UPC), Barcelona, Spain"}]},{"given":"Jordi","family":"Vil\u00e0-Valls","sequence":"additional","affiliation":[{"name":"Centre Tecnol\u00f2gic de Telecomunicacions de Catalunya (CTTC), Barcelona, Spain"}]},{"given":"Ana","family":"Moragrega","sequence":"additional","affiliation":[{"name":"Centre Tecnol\u00f2gic de Telecomunicacions de Catalunya (CTTC), Barcelona, Spain"}]},{"given":"Pau","family":"Closas","sequence":"additional","affiliation":[{"name":"Northeastern University, Boston, MA, USA"}]},{"given":"Juan A","family":"Fernandez-Rubio","sequence":"additional","affiliation":[{"name":"Universitat Polit\u00e8cnica de Catalunya (UPC), Barcelona, Spain"}]}],"member":"179","published-online":{"date-parts":[[2017,8,29]]},"reference":[{"key":"bibr1-1550147717722158","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2015.2403868"},{"key":"bibr2-1550147717722158","volume-title":"Algorithms and methods for received signal strength based wireless localization","author":"Jukka Talvitie J","year":"2015"},{"key":"bibr3-1550147717722158","volume-title":"Indoor radio channel propagation modelling by ray tracing techniques","author":"Laurenson 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