{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T21:25:04Z","timestamp":1790112304886,"version":"4.0.1"},"reference-count":25,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2024,1,27]],"date-time":"2024-01-27T00:00:00Z","timestamp":1706313600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The zero-velocity update (ZUPT) algorithm is a pivotal advancement in pedestrian navigation accuracy, utilizing foot-mounted inertial sensors. Its key issue hinges on accurately identifying periods of zero-velocity during human movement. This paper introduces an innovative adaptive sliding window technique, leveraging the Fourier Transform to precisely isolate the pedestrian\u2019s gait frequency from spectral data. Building on this, the algorithm adaptively adjusts the zero-velocity detection threshold in accordance with the identified gait frequency. This adaptation significantly refines the accuracy in detecting zero-velocity intervals. Experimental evaluations reveal that this method outperforms traditional fixed-threshold approaches by enhancing precision and minimizing false positives. Experiments on single-step estimation show the adaptability of the algorithm to motion states such as slow, fast, and running. Additionally, the paper demonstrates pedestrian trajectory localization experiments under a variety of walking conditions. These tests confirm that the proposed method substantially improves the performance of the ZUPT algorithm, highlighting its potential for pedestrian navigation systems.<\/jats:p>","DOI":"10.3390\/s24030838","type":"journal-article","created":{"date-parts":[[2024,1,30]],"date-time":"2024-01-30T12:06:58Z","timestamp":1706616418000},"page":"838","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["A Novel Zero-Velocity Interval Detection Algorithm for a Pedestrian Navigation System with Foot-Mounted Inertial Sensors"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4131-7763","authenticated-orcid":false,"given":"Xiaotao","family":"Wang","sequence":"first","affiliation":[{"name":"College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiacheng","family":"Li","sequence":"additional","affiliation":[{"name":"College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guangfei","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xingyu","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1415","DOI":"10.1007\/s42835-021-00957-5","article-title":"High Precision Indoor Positioning System Based on UWB\/MINS Integration in NLOS Condition","volume":"17","author":"Yao","year":"2022","journal-title":"J. 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