{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T10:12:50Z","timestamp":1776334370260,"version":"3.51.2"},"reference-count":28,"publisher":"SAGE Publications","issue":"6","license":[{"start":{"date-parts":[[2018,6,1]],"date-time":"2018-06-01T00:00:00Z","timestamp":1527811200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2016YFB0502102"],"award-info":[{"award-number":["2016YFB0502102"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"crossref","award":["KYLX16_0544"],"award-info":[{"award-number":["KYLX16_0544"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2016M601909"],"award-info":[{"award-number":["2016M601909"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41674030"],"award-info":[{"award-number":["41674030"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Distributed Sensor Networks"],"published-print":{"date-parts":[[2018,6]]},"abstract":"<jats:p> There are many factors affecting Wi-Fi signal in indoor environment, among which the human body has an important impact. And, its characteristic is related to the user\u2019s orientation. To eliminate positioning errors caused by user\u2019s human body and improve positioning accuracy, this study puts forward an adaptive weighted K-nearest neighbor fingerprint positioning method considering the user\u2019s orientation. First, the orientation fingerprint database model is proposed, which includes the position, orientation, and the sequence of mean received signal strength indicator at each reference point. Second, the fuzzy c-means algorithm is used to cluster orientation fingerprint database taking the hybrid distance of the signal domain and position domain as the clustering feature. Finally, the proposed adaptive algorithm is developed to select K-reference points by matching operation, to remove the reference points with larger signal-domain distances, minimum and maximum coordinate values, and calculate the weighted mean coordinates of the remaining reference points for positioning results. The experimental results show that the average error decreases by 0.7\u2009m, and the root mean square error decreases to about 1.3\u2009m by the proposed technique. And, we conclude that the proposed adaptive weighted K-nearest neighbor fingerprint positioning method can improve positioning accuracy. <\/jats:p>","DOI":"10.1177\/1550147718785885","type":"journal-article","created":{"date-parts":[[2018,6,29]],"date-time":"2018-06-29T06:48:44Z","timestamp":1530254924000},"page":"155014771878588","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":17,"title":["A novel method of adaptive weighted <i>K<\/i>-nearest neighbor fingerprint indoor positioning considering user\u2019s orientation"],"prefix":"10.1177","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2964-7698","authenticated-orcid":false,"given":"Jingxue","family":"Bi","sequence":"first","affiliation":[{"name":"NASG Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou, China"},{"name":"School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunjia","family":"Wang","sequence":"additional","affiliation":[{"name":"NASG Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou, China"},{"name":"School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Li","sequence":"additional","affiliation":[{"name":"School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongji","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongxia","family":"Qi","sequence":"additional","affiliation":[{"name":"School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongkang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2018,6,28]]},"reference":[{"key":"bibr1-1550147718785885","unstructured":"Connolly P, Boone D. 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