Radiometric and Geometric Calibration of an Inexpensive LED-Based Lidar Sensor

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dc.contributor.advisorGlennie, Craig L.
dc.contributor.committeeMemberHartzell, Preston J.
dc.contributor.committeeMemberLee, Hyongki
dc.contributor.committeeMemberWright, William C.
dc.creatorLaughlin, Jordan
dc.creator.orcid0000-0003-1232-4523
dc.date.accessioned2020-06-02T04:26:45Z
dc.date.createdMay 2020
dc.date.issued2020-05
dc.date.submittedMay 2020
dc.date.updated2020-06-02T04:26:45Z
dc.description.abstractRadiometric calibration of traditional lidar sensors that employ direct time of flight or phase-based ranging is well established. However, emerging inexpensive, lightweight, short-range lidar sensors that utilize non-traditional ranging methods report measurements that are not appropriate for existing radiometric calibration techniques. One such sensor, the TeraRanger Evo 60m by Terabee is a light emitting diode (instead of laser) lidar sensor with an automatically varying collection rate. This thesis investigates the performance of a new radiometric calibration model, one based on a neural network, applied to the Evo 60m. Application of the proposed radiometric calibration model resulted in performance similar to traditional lidar sensors, with mean differences in reflectance of no more than 5% and root mean square errors of no more than 6% for non-specular targets. The radiometric calibration model provides a generic approach that may be applicable to other low-cost lidar sensors and is a potential stepping stone toward development of a low-cost, multiple wavelength (multispectral) lidar sensor. The ranging performance of the Evo 60m was also evaluated in this work. Three of the four sensors evaluated fall below the manufacturer’s stated accuracy level of ±40 millimeters while one lies just above the threshold at ±43 millimeters.
dc.description.departmentCivil and Environmental Engineering, Department of
dc.format.digitalOriginborn digital
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/10657/6597
dc.language.isoeng
dc.rightsThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.subjectLidar
dc.subjectRadiometric Calibration
dc.subjectNeural Networks
dc.subjectMachine Learning
dc.subjectGeometric Calibration
dc.titleRadiometric and Geometric Calibration of an Inexpensive LED-Based Lidar Sensor
dc.type.dcmiText
dc.type.genreThesis
local.embargo.lift2022-05-01
local.embargo.terms2022-05-01
thesis.degree.collegeCullen College of Engineering
thesis.degree.departmentCivil and Environmental Engineering, Department of
thesis.degree.disciplineGeosensing Systems Engineering
thesis.degree.grantorUniversity of Houston
thesis.degree.levelMasters
thesis.degree.nameMaster of Science

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