{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,16]],"date-time":"2024-07-16T00:22:12Z","timestamp":1721089332039},"reference-count":50,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2024,7,15]],"date-time":"2024-07-15T00:00:00Z","timestamp":1721001600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Hebei Province Higher Education Science and Technology Research Key Project","award":["ZD2022076"]},{"name":"Research Start-up Fund Project of Tianjin University of Technology and Education","award":["KYQD202403"]},{"name":"Scientific Research Project of Tianjin Municipal Education Commission","award":["2022ZD018"]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61702071"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"There are various indoor fingerprint localization techniques utilizing the similarity of received signal strength (RSS) to discriminate the similarity of positions. However, due to the varied states of different wireless access points (APs), each AP\u2019s contribution to RSS similarity varies, which affects the accuracy of localization. In our study, we analyzed several critical causes that affect APs\u2019 contribution, including APs\u2019 health states and APs\u2019 positions. Inspired by these insights, for a large-scale indoor space with ubiquitous APs, a threshold was set for all sample RSS to eliminate the abnormal APs dynamically, a correction quantity for each RSS was provided by the distance between the AP and the sample position to emphasize closer APs, and a priority weight was designed by RSS differences (RSSD) to further optimize the capability of fingerprint distances (FDs, the Euclidean distance of RSS) to discriminate physical distance (PDs, the Euclidean distance of positions). Integrating the above policies for the classical WKNN algorithm, a new indoor fingerprint localization technique is redefined, referred to as FDs\u2019 discrimination capability improvement WKNN (FDDC-WKNN). Our simulation results showed that the correlation and consistency between FDs and PDs are well improved, with the strong correlation increasing from 0 to 76% and the high consistency increasing from 26% to 99%, which confirms that the proposed policies can greatly enhance the discrimination capabilities of RSS similarity. We also found that abnormal APs can cause significant impact on FDs discrimination capability. Further, by implementing the FDDC-WKNN algorithm in experiments, we obtained the optimal K value in both the simulation scene and real library scene, under which the mean errors have been reduced from 2.2732 m to 1.2290 m and from 4.0489 m to 2.4320 m, respectively. In addition, compared to not using the FDDC-WKNN, the cumulative distribution function (CDF) of the localization errors curve converged faster and the error fluctuation was smaller, which demonstrates the FDDC-WKNN having stronger robustness and more stable localization performance.<\/jats:p>","DOI":"10.3390\/s24144586","type":"journal-article","created":{"date-parts":[[2024,7,15]],"date-time":"2024-07-15T19:17:06Z","timestamp":1721071026000},"page":"4586","source":"Crossref","is-referenced-by-count":0,"title":["A WKNN Indoor Fingerprint Localization Technique Based on Improved Discrimination Capability of RSS Similarity"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"http:\/\/orcid.org\/0000-0003-0763-7656","authenticated-orcid":false,"given":"Baofeng","family":"Wang","sequence":"first","affiliation":[{"name":"School of Information Technology Engineering, Tianjin University of Technology and Education, Tianjin 300222, China"}]},{"given":"Qinghai","family":"Li","sequence":"additional","affiliation":[{"name":"School of Information Technology Engineering, Tianjin University of Technology and Education, Tianjin 300222, China"}]},{"given":"Jia","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Information Technology Engineering, Tianjin University of Technology and Education, Tianjin 300222, China"},{"name":"School of Information Technology Engineering, Hebei University of Environmental Engineering, Qinhuangdao 066102, China"}]},{"given":"Zumin","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Dalian University, Dalian 116600, China"}]},{"given":"Qiudong","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Information Technology Engineering, Tianjin University of Technology and Education, Tianjin 300222, China"}]},{"given":"Rui","family":"Liang","sequence":"additional","affiliation":[{"name":"School of Information Technology Engineering, Tianjin University of Technology and Education, Tianjin 300222, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1007\/s11277-021-08209-5","article-title":"A review of indoor localization techniques and wireless technologies","volume":"119","author":"Obeidat","year":"2021","journal-title":"Wirel. 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