{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T09:13:27Z","timestamp":1772788407081,"version":"3.50.1"},"reference-count":21,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2022,10,20]],"date-time":"2022-10-20T00:00:00Z","timestamp":1666224000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China (NSFC)","doi-asserted-by":"publisher","award":["41971413"],"award-info":[{"award-number":["41971413"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China (NSFC)","doi-asserted-by":"publisher","award":["U1934215"],"award-info":[{"award-number":["U1934215"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China (NSFC)","doi-asserted-by":"publisher","award":["2021YJ047"],"award-info":[{"award-number":["2021YJ047"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"China Academy of Railway Sciences Corporation Limited","award":["41971413"],"award-info":[{"award-number":["41971413"]}]},{"name":"China Academy of Railway Sciences Corporation Limited","award":["U1934215"],"award-info":[{"award-number":["U1934215"]}]},{"name":"China Academy of Railway Sciences Corporation Limited","award":["2021YJ047"],"award-info":[{"award-number":["2021YJ047"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>UAV LiDAR is a powerful tool for rapidly acquiring ground-based 3D spatial information and has been used in various applications. In addition to the ranging mechanism, the scanning method is also an important factor, affecting the performance of UAV LiDAR, and the internal angle error of LiDAR will seriously affect its measurement accuracy. Starting from the rotary scanning model of a single-sided mirror, this paper presents a comparative study of the characteristics of 45\u00b0 single-sided mirror scanning, polygon prism scanning, polygon tower mirror scanning, and wedge mirror scanning. The error sources of the quadrangular tower mirror scanning are analyzed in detail, including the angle deviation between the direction of emitted laser and the rotation axis (typical 0.13 \u00b1 0.18\u00b0 and 0.85\u00b0 \u00b1 0.26\u00b0), the angle deviation between the mirror\u2019s reflection plane and the rotation axis, and the surface angle deviation between multiple surfaces (typical \u00b1 0.06\u00b0). As a result, the measurement deviation caused by the internal angle error can be as high as decimeter to meter, which cannot be fully compensated by simply adjusting the installation angle between the UAV and the LiDAR. After the calibration of the internal angle error, the standard deviation of the elevation difference between the point cloud and the control point is only 0.024\u00a0m in the flight experiment at 300\u00a0m altitude.<\/jats:p>","DOI":"10.3390\/rs14205260","type":"journal-article","created":{"date-parts":[[2022,10,21]],"date-time":"2022-10-21T00:34:30Z","timestamp":1666312470000},"page":"5260","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Analysis of Internal Angle Error of UAV LiDAR Based on Rotating Mirror Scanning"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4673-5569","authenticated-orcid":false,"given":"Hao","family":"Zhou","sequence":"first","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7948-2828","authenticated-orcid":false,"given":"Qingzhou","family":"Mao","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yufei","family":"Song","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anlei","family":"Wu","sequence":"additional","affiliation":[{"name":"Wuhan Luojia Yiyun Photoelectric Technology Co., Ltd., Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xueqing","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1109\/JSTARS.2016.2543464","article-title":"LiDAR Data Filtering and DTM Generation Using Empirical Mode Decomposition","volume":"10","author":"Ozcan","year":"2017","journal-title":"IEEE J. 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