{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:52:10Z","timestamp":1760241130968,"version":"build-2065373602"},"reference-count":20,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2019,12,3]],"date-time":"2019-12-03T00:00:00Z","timestamp":1575331200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System","award":["the State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System"],"award-info":[{"award-number":["the State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System"]}]},{"name":"Yong Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region","award":["Yong Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region"],"award-info":[{"award-number":["Yong Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61502254"],"award-info":[{"award-number":["61502254"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>When detecting micro-distortion of lidar scanning signals, current hardwires and algorithms have low compatibility, resulting in slow detection speed, high energy consumption, and poor performance against interference. A geometric statistics-based micro-distortion detection technology for lidar scanning signals was proposed. The proposed method built the overall framework of the technology, used TCD1209DG (made by TOSHIBA, Tokyo, Japan) to implement a linear array CCD (charge-coupled device) module for photoelectric conversion, signal charge storage, and transfer. Chip FPGA was used as the core component of the signal processing module for signal preprocessing of TCD1209DG output. Signal transmission units were designed with chip C8051, FT232, and RS-485 to perform lossless signal transmission between the host and any slave. The signal distortion feature matching algorithm based on geometric statistics was adopted. Micro-distortion detection of lidar scanning signals was achieved by extracting, counting, and matching the distorted signals. The correction of distorted signals was implemented with the proposed method. Experimental results showed that the proposed method had faster detection speed, lower detection energy consumption, and stronger anti-interference ability, which effectively improved micro-distortion correction.<\/jats:p>","DOI":"10.3390\/sym11121471","type":"journal-article","created":{"date-parts":[[2019,12,4]],"date-time":"2019-12-04T04:30:35Z","timestamp":1575433835000},"page":"1471","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Micro-Distortion Detection of Lidar Scanning Signals Based on Geometric Analysis"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9909-0664","authenticated-orcid":false,"given":"Shuai","family":"Liu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, Luoyang 471000, China"},{"name":"College of Computer Science, Inner Mongolia University, Hohhot 010012, China"},{"name":"College of Information Science and Engineering, Hunan Normal University, Changsha 410081, China"}]},{"given":"Xiang","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, Luoyang 471000, China"}]},{"given":"Ying","family":"Li","sequence":"additional","affiliation":[{"name":"College of information and communication engineering, Harbin Engineering University, Harbin 150000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0371-9646","authenticated-orcid":false,"given":"Xiaochun","family":"Cheng","sequence":"additional","affiliation":[{"name":"College of Computer Science, Middlesex University, London NW4 4BT, UK"}]}],"member":"1968","published-online":{"date-parts":[[2019,12,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"907","DOI":"10.1109\/TSP.2017.2757913","article-title":"Geometric Approach to Covariance Matrix Estimation and its Applications to Radar Problems","volume":"66","author":"Aubry","year":"2018","journal-title":"IEEE Trans. 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