{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T16:04:23Z","timestamp":1774541063736,"version":"3.50.1"},"reference-count":22,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,1,5]],"date-time":"2022-01-05T00:00:00Z","timestamp":1641340800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key Research and Development Program of China","award":["2018YFF0216004"],"award-info":[{"award-number":["2018YFF0216004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The indoor autonomous navigation of unmanned aerial vehicles (UAVs) is the current research hotspot. Unlike the outdoor broad environment, the indoor environment is unknown and complicated. Global Navigation Satellite System (GNSS) signals are easily blocked and reflected because of complex indoor spatial features, which make it impossible to achieve positioning and navigation indoors relying on GNSS. This article proposes a set of indoor corridor environment positioning methods based on the integration of WiFi and IMU. The zone partition-based Weighted K Nearest Neighbors (WKNN) algorithm is used to achieve higher WiFi-based positioning accuracy. On the basis of the Error-State Kalman Filter (ESKF) algorithm, WiFi-based and IMU-based methods are fused together and realize higher positioning accuracy. The probability-based optimization method is used for further accuracy improvement. After data fusion, the positioning accuracy increased by 51.09% compared to the IMU-based algorithm and by 66.16% compared to the WiFi-based algorithm. After optimization, the positioning accuracy increased by 20.9% compared to the ESKF-based data fusion algorithm. All of the above results prove that methods based on WiFi and IMU (low-cost sensors) are very capable of obtaining high indoor positioning accuracy.<\/jats:p>","DOI":"10.3390\/s22010391","type":"journal-article","created":{"date-parts":[[2022,1,9]],"date-time":"2022-01-09T23:08:26Z","timestamp":1641769706000},"page":"391","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Constrained ESKF for UAV Positioning in Indoor Corridor Environment Based on IMU and WiFi"],"prefix":"10.3390","volume":"22","author":[{"given":"Zhonghan","family":"Li","sequence":"first","affiliation":[{"name":"School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8730-8440","authenticated-orcid":false,"given":"Yongbo","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China"},{"name":"Aircraft and Propulsion Laboratory, Ningbo Institute of Technology, Beihang University, Ningbo 315100, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1446","DOI":"10.1016\/j.proeng.2011.08.268","article-title":"The research of indoor navigation system using pseudolites","volume":"15","author":"Wan","year":"2011","journal-title":"Procedia Eng."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"48","DOI":"10.5081\/jgps.1.1.48","article-title":"Pseudolite applications in positioning and navigation: Pro-gress and problems","volume":"1","author":"Wang","year":"2002","journal-title":"Positioning"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1109\/MRA.2012.2206473","article-title":"Toward a Fully Autonomous UAV: Research Platform for Indoor and Outdoor Urban Search and Rescue","volume":"19","author":"Tomic","year":"2012","journal-title":"IEEE Robot. 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