A Calibration Method for Time Dimension and Space Dimension of Streak Tube Imaging Lidar
-
Published:2023-09-06
Issue:18
Volume:13
Page:10042
-
ISSN:2076-3417
-
Container-title:Applied Sciences
-
language:en
-
Short-container-title:Applied Sciences
Author:
Chen Zhaodong1, Shao Fangfang1, Fan Zhigang2, Wang Xing1, Dong Chaowei1, Dong Zhiwei1, Fan Rongwei1, Chen Deying1
Affiliation:
1. National Key Laboratory of Science and Technology on Tunable Laser, Harbin Institute of Technology, Harbin 150080, China 2. Research Center for Space Optical Engineering, School of Astronautics, Harbin Institute of Technology, Harbin 150001, China
Abstract
Owing to the special working systems of streak tube imaging lidar (STIL), the time and space dimensions are coupled together on the streak images. This coupling can cause measurement errors in 3D point clouds and can make measurement results more complicated to calibrate than other kinds of lidars. This paper presents a method to generate a time calibration array and an angle calibration array to separate the offset of the streak into time dimension and space dimension. The time and space information of the signal at any position on the streak image can be indexed through these two arrays. A validation experiment on aircraft was carried out, and the range error of the 3D point cloud was improved from 0.41 m to 0.27 m using the proposed calibration method. Thus, using the proposed calibration method can improve the accuracy of the point cloud produced by STIL.
Funder
National Natural Science Foundation of China
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Reference21 articles.
1. Using LiDAR for digital documentation of ancient city walls;Cheng;J. Cult. Herit.,2016 2. Du, M., Li, H., and Roshanianfard, A. (2022). Design and Experimental Study on an Innovative UAV-LiDAR Topographic Mapping System for Precision Land Levelling. Drones, 6. 3. Spatial and temporal domain filtering for underwater lidar;Jantzi;J. Opt. Soc. Am. A,2021 4. Collings, S., Martin, T.J., Hernandez, E., Edwards, S., Filisetti, A., Catt, G., Marouchos, A., Boyd, M., and Embry, C. (2020). Findings from a Combined Subsea LiDAR and Multibeam Survey at Kingston Reef, Western Australia. Remote Sens., 12. 5. Palacin, J., Martinez, D., Rubies, E., and Clotet, E. (2020). Mobile Robot Self-Localization with 2D Push-Broom LIDAR in a 2D Map. Sensors, 20.
|
|