{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T18:43:53Z","timestamp":1785437033730,"version":"3.56.0"},"reference-count":26,"publisher":"Optica Publishing Group","issue":"15","license":[{"start":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T00:00:00Z","timestamp":1784592000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/doi.org\/10.1364\/OA_License_v2#VOR"},{"start":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T00:00:00Z","timestamp":1784592000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/opg.optica.org\/policies\/opg-tdm-policy.json"}],"funder":[{"name":"National Key Research and Development Plan","award":["ZDYF20230043"],"award-info":[{"award-number":["ZDYF20230043"]}]},{"DOI":"10.13039\/501100017700","name":"Henan Province Science and Technology Research Project","doi-asserted-by":"crossref","award":["262102211123"],"award-info":[{"award-number":["262102211123"]}],"id":[{"id":"10.13039\/501100017700","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100006407","name":"Henan Province Natural Science Foundation","doi-asserted-by":"crossref","award":["262300422526"],"award-info":[{"award-number":["262300422526"]}],"id":[{"id":"10.13039\/501100006407","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["opg.optica.org"],"crossmark-restriction":false},"short-container-title":["Opt. Lett."],"published-print":{"date-parts":[[2026,8,1]]},"abstract":"<jats:p>Rotational Doppler velocimetry (RDV) has emerged as a key technique for sensing and identifying spinning objects. However, existing fiber-based RDV systems generally rely on customized mode-selective couplers for orbital-angular-momentum generation or mode filtering, resulting in increased complexity and cost. Here, we propose a fiber-assisted RDV scheme that combines Gaussian-mode emission, multimode-fiber (MMF) reception, and Doppler-interval analysis without requiring such devices. The scheme is theoretically analyzed and experimentally demonstrated over a rotational-speed range of 0\u20135000 r\/min. Spectral autocorrelation enables robust interval extraction, yielding relative errors below 0.2% and standard deviations below 5 r\/min. Robust operation is further verified under lateral displacement, angular misalignment, and varying surface roughness. Moreover, larger MMF core diameters are shown to enhance optical collection and improve signal-to-noise ratio. These results demonstrate a simple, low-cost, and practical route toward engineering-oriented rotational Doppler LiDAR systems.<\/jats:p>","DOI":"10.1364\/ol.601850","type":"journal-article","created":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T12:01:39Z","timestamp":1783339299000},"page":"4172","update-policy":"https:\/\/doi.org\/10.1364\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Integration of Gaussian-mode emission and multimode fiber reception with Doppler-shifted interval analysis for rotational velocity detection"],"prefix":"10.1364","volume":"51","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8619-4699","authenticated-orcid":true,"given":"Yanxiang","family":"Zhang","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/01yqg2h08","id-type":"ROR","asserted-by":"publisher"}]},{"name":"Harbin Institute of Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongkang","family":"Dong","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/01yqg2h08","id-type":"ROR","asserted-by":"publisher"}]},{"name":"Harbin Institute of Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"285","published-online":{"date-parts":[[2026,7,21]]},"reference":[{"key":"ol-51-15-4172-R1","doi-asserted-by":"publisher","first-page":"596","DOI":"10.4028\/www.scientific.net\/AMM.427-429.596","type":"journal-article","volume":"427","author":"Kuang","year":"2013","journal-title":"Appl. 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All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.","name":"copyright","label":"Copyright"}]}}