Rigorous Boresight Self-Calibration of Mobile and UAV LiDAR Scanning Systems by Strip Adjustment

Mobile LiDAR Scanning (MLS) systems and UAV LiDAR Scanning (ULS) systems equipped with precise Global Navigation Satellite System (GNSS)/Inertial Measurement Unit (IMU) positioning units and LiDAR sensors are used at an increasing rate for the acquisition of high density and high accuracy point clou...

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Main Authors: Zhen Li, Junxiang Tan, Hua Liu
Format: Article
Language:English
Published: MDPI AG 2019-02-01
Series:Remote Sensing
Subjects:
ICP
Online Access:https://www.mdpi.com/2072-4292/11/4/442
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spelling doaj-7e8aa1eabbb9490396a13885a179c1fe2020-11-25T00:02:55ZengMDPI AGRemote Sensing2072-42922019-02-0111444210.3390/rs11040442rs11040442Rigorous Boresight Self-Calibration of Mobile and UAV LiDAR Scanning Systems by Strip AdjustmentZhen Li0Junxiang Tan1Hua Liu2School of Hydraulic, Energy and Power Engineering, Yangzhou University, Jiangyang Middle Road 131, Yangzhou 225127, ChinaCollege of Earth Sciences, Chengdu University of Technology, Erxianqiao Dongsan Road 1, Chengdu 610059, ChinaSchool of Geodesy and Geomatics, Wuhan University, Luoyu Road 129, Wuhan 430079, ChinaMobile LiDAR Scanning (MLS) systems and UAV LiDAR Scanning (ULS) systems equipped with precise Global Navigation Satellite System (GNSS)/Inertial Measurement Unit (IMU) positioning units and LiDAR sensors are used at an increasing rate for the acquisition of high density and high accuracy point clouds because of their safety and efficiency. Without careful calibration of the boresight angles of the MLS systems and ULS systems, the accuracy of data acquired would degrade severely. This paper proposes an automatic boresight self-calibration method for the MLS systems and ULS systems using acquired multi-strip point clouds. The boresight angles of MLS systems and ULS systems are expressed in the direct geo-referencing equation and corrected by minimizing the misalignments between points scanned from different directions and different strips. Two datasets scanned by MLS systems and two datasets scanned by ULS systems were used to verify the proposed boresight calibration method. The experimental results show that the root mean square errors (RMSE) of misalignments between point correspondences of the four datasets after boresight calibration are 2.1 cm, 3.4 cm, 5.4 cm, and 6.1 cm, respectively, which are reduced by 59.6%, 75.4%, 78.0%, and 94.8% compared with those before boresight calibration.https://www.mdpi.com/2072-4292/11/4/442mobile LiDAR scanningUAV LiDAR scanningboresight calibrationstrip adjustmentICP
collection DOAJ
language English
format Article
sources DOAJ
author Zhen Li
Junxiang Tan
Hua Liu
spellingShingle Zhen Li
Junxiang Tan
Hua Liu
Rigorous Boresight Self-Calibration of Mobile and UAV LiDAR Scanning Systems by Strip Adjustment
Remote Sensing
mobile LiDAR scanning
UAV LiDAR scanning
boresight calibration
strip adjustment
ICP
author_facet Zhen Li
Junxiang Tan
Hua Liu
author_sort Zhen Li
title Rigorous Boresight Self-Calibration of Mobile and UAV LiDAR Scanning Systems by Strip Adjustment
title_short Rigorous Boresight Self-Calibration of Mobile and UAV LiDAR Scanning Systems by Strip Adjustment
title_full Rigorous Boresight Self-Calibration of Mobile and UAV LiDAR Scanning Systems by Strip Adjustment
title_fullStr Rigorous Boresight Self-Calibration of Mobile and UAV LiDAR Scanning Systems by Strip Adjustment
title_full_unstemmed Rigorous Boresight Self-Calibration of Mobile and UAV LiDAR Scanning Systems by Strip Adjustment
title_sort rigorous boresight self-calibration of mobile and uav lidar scanning systems by strip adjustment
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2019-02-01
description Mobile LiDAR Scanning (MLS) systems and UAV LiDAR Scanning (ULS) systems equipped with precise Global Navigation Satellite System (GNSS)/Inertial Measurement Unit (IMU) positioning units and LiDAR sensors are used at an increasing rate for the acquisition of high density and high accuracy point clouds because of their safety and efficiency. Without careful calibration of the boresight angles of the MLS systems and ULS systems, the accuracy of data acquired would degrade severely. This paper proposes an automatic boresight self-calibration method for the MLS systems and ULS systems using acquired multi-strip point clouds. The boresight angles of MLS systems and ULS systems are expressed in the direct geo-referencing equation and corrected by minimizing the misalignments between points scanned from different directions and different strips. Two datasets scanned by MLS systems and two datasets scanned by ULS systems were used to verify the proposed boresight calibration method. The experimental results show that the root mean square errors (RMSE) of misalignments between point correspondences of the four datasets after boresight calibration are 2.1 cm, 3.4 cm, 5.4 cm, and 6.1 cm, respectively, which are reduced by 59.6%, 75.4%, 78.0%, and 94.8% compared with those before boresight calibration.
topic mobile LiDAR scanning
UAV LiDAR scanning
boresight calibration
strip adjustment
ICP
url https://www.mdpi.com/2072-4292/11/4/442
work_keys_str_mv AT zhenli rigorousboresightselfcalibrationofmobileanduavlidarscanningsystemsbystripadjustment
AT junxiangtan rigorousboresightselfcalibrationofmobileanduavlidarscanningsystemsbystripadjustment
AT hualiu rigorousboresightselfcalibrationofmobileanduavlidarscanningsystemsbystripadjustment
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