Estimation of biases in lidar system calibration parameters using overlapping strips

2010 ◽  
Vol 36 (sup2) ◽  
pp. S335-S354 ◽  
Author(s):  
Ki In Bang ◽  
Ayman Habib ◽  
Ana Kersting
Keyword(s):  
Lidar System ◽  
System Calibration ◽  
Calibration Parameters

scholarly journals Alternative Methodologies for LiDAR System Calibration

2010 ◽  
Vol 2 (3) ◽  
pp. 874-907 ◽  
Author(s):  
Ayman Habib ◽  
Ki In Bang ◽  
Ana Paula Kersting ◽  
Jacky Chow
Keyword(s):  
Lidar System ◽  
System Calibration

scholarly journals Computer and Physical Modeling for Verification of the Stereo System Calibration Parameters Optimization Results

2021 ◽  
Author(s):  
Vladislav Pinchukov ◽  
Ekaterina Shmatko ◽  
Anton Poroykov ◽  
Artem Bogachev
Keyword(s):  
Physical Modeling ◽  
Video Camera ◽  
Parameters Optimization ◽  
Surface Shape ◽  
Experimental Investigations ◽  
System Calibration ◽  
Video Cameras ◽  
Close Range ◽  
Optimizing Algorithm ◽  
Calibration Parameters

Close-range photogrammetry is widely used to measure surface shapes and diagnose deformation. Usually, a stereo system of video cameras is used to register images of the measured object from several different angles. The surface shape is determined by triangulating a set of 2D points from these images. Triangulation uses the stereo system calibration parameters, which are determined before the experiment. Measurements during conditions with increased vibration loads can lead to a change in the relative position of the cameras of the stereo system (decalibration). This leads to a change in the actual calibration parameters and an increase in the measurement error. The decalibration problem can be solved using multidimensional optimization algorithms. To verify their calculation's results it is proposed to use a computer and physical modeling of decalibration of a video camera stereo system in laboratory conditions. The paper presents the implementation of the optimizing algorithm for the external parameters of a stereo system and the results of its performance during the experimental investigations.

scholarly journals GNSS/INS-Assisted Structure from Motion Strategies for UAV-Based Imagery over Mechanized Agricultural Fields

2020 ◽  
Vol 12 (3) ◽  
pp. 351 ◽  
Author(s):  
Seyyed Meghdad Hasheminasab ◽  
Tian Zhou ◽  
Ayman Habib
Keyword(s):  
3D Reconstruction ◽  
Structure From Motion ◽  
Point Clouds ◽  
Bundle Adjustment ◽  
Agricultural Fields ◽  
System Calibration ◽  
3D Point Clouds ◽  
Digital Agriculture ◽  
Orientation Parameters ◽  
Calibration Parameters

Acquired imagery by unmanned aerial vehicles (UAVs) has been widely used for three-dimensional (3D) reconstruction/modeling in various digital agriculture applications, such as phenotyping, crop monitoring, and yield prediction. 3D reconstruction from well-textured UAV-based images has matured and the user community has access to several commercial and opensource tools that provide accurate products at a high level of automation. However, in some applications, such as digital agriculture, due to repetitive image patterns, these approaches are not always able to produce reliable/complete products. The main limitation of these techniques is their inability to establish a sufficient number of correctly matched features among overlapping images, causing incomplete and/or inaccurate 3D reconstruction. This paper provides two structure from motion (SfM) strategies, which use trajectory information provided by an onboard survey-grade global navigation satellite system/inertial navigation system (GNSS/INS) and system calibration parameters. The main difference between the proposed strategies is that the first one—denoted as partially GNSS/INS-assisted SfM—implements the four stages of an automated triangulation procedure, namely, imaging matching, relative orientation parameters (ROPs) estimation, exterior orientation parameters (EOPs) recovery, and bundle adjustment (BA). The second strategy— denoted as fully GNSS/INS-assisted SfM—removes the EOPs estimation step while introducing a random sample consensus (RANSAC)-based strategy for removing matching outliers before the BA stage. Both strategies modify the image matching by restricting the search space for conjugate points. They also implement a linear procedure for ROPs’ refinement. Finally, they use the GNSS/INS information in modified collinearity equations for a simpler BA procedure that could be used for refining system calibration parameters. Eight datasets over six agricultural fields are used to evaluate the performance of the developed strategies. In comparison with a traditional SfM framework and Pix4D Mapper Pro, the proposed strategies are able to generate denser and more accurate 3D point clouds as well as orthophotos without any gaps.

Characterization of system calibration parameters for high gain dual polarization satellite beacon diagnostics of ionospheric variations

Radio Science ◽  
2011 ◽  
Vol 46 (5) ◽  
pp. n/a-n/a ◽  
Author(s):  
James P. Anderson ◽  
Eric B. Phelps ◽  
Philip J. Erickson ◽  
Frank D. Lind ◽  
Anthea J. Coster ◽  
...  
Keyword(s):  
High Gain ◽  
Dual Polarization ◽  
System Calibration ◽  
Satellite Beacon ◽  
Calibration Parameters

scholarly journals COMPARATIVE ANALYSIS OF DIFFERENT LIDAR SYSTEM CALIBRATION TECHNIQUES

2016 ◽  
Vol XLI-B1 ◽  
pp. 229-235
Author(s):  
M. Miller ◽  
A. Habib
Keyword(s):  
Systematic Errors ◽  
Airborne Lidar ◽  
Data Availability ◽  
Lidar System ◽  
Math Model ◽  
System Calibration ◽  
Calibration Methods ◽  
Using Data ◽  
Calibration Techniques ◽  
Control Surfaces

With light detection and ranging (LiDAR) now being a crucial tool for engineering products and on the fly spatial analysis, it is necessary for the user community to have standardized calibration methods. The three methods in this study were developed and proven by the Digital Photogrammetry Research Group (DPRG) for airborne LiDAR systems and are as follows; Simplified, Quasi-Rigorous, and Rigorous. In lieu of using expensive control surfaces for calibration, these methods compare overlapping LiDAR strips to estimate the systematic errors. These systematic errors are quantified by these methods and include the lever arm biases, boresight biases, range bias and scan angle scale bias. These three methods comprehensively represent all of the possible flight configurations and data availability and this paper will test the limits of the method with the most assumptions, the simplified calibration, by using data that violates the assumptions it’s math model is based on and compares the results to the quasi-rigorous and rigorous techniques. The overarching goal is to provide a LiDAR system calibration that does not require raw measurements which can be carried out with minimal control and flight lines to reduce costs. This testing is unique because the terrain used for calibration does not contain gable roofs, all other LiDAR system calibration testing and development has been done with terrain containing features with high geometric integrity such as gable roofs.

scholarly journals COMPARATIVE ANALYSIS OF DIFFERENT LIDAR SYSTEM CALIBRATION TECHNIQUES

2016 ◽  
Vol XLI-B1 ◽  
pp. 229-235
Author(s):  
M. Miller ◽  
A. Habib
Keyword(s):  
Systematic Errors ◽  
Airborne Lidar ◽  
Data Availability ◽  
Lidar System ◽  
Math Model ◽  
System Calibration ◽  
Calibration Methods ◽  
Using Data ◽  
Calibration Techniques ◽  
Control Surfaces

With light detection and ranging (LiDAR) now being a crucial tool for engineering products and on the fly spatial analysis, it is necessary for the user community to have standardized calibration methods. The three methods in this study were developed and proven by the Digital Photogrammetry Research Group (DPRG) for airborne LiDAR systems and are as follows; Simplified, Quasi-Rigorous, and Rigorous. In lieu of using expensive control surfaces for calibration, these methods compare overlapping LiDAR strips to estimate the systematic errors. These systematic errors are quantified by these methods and include the lever arm biases, boresight biases, range bias and scan angle scale bias. These three methods comprehensively represent all of the possible flight configurations and data availability and this paper will test the limits of the method with the most assumptions, the simplified calibration, by using data that violates the assumptions it’s math model is based on and compares the results to the quasi-rigorous and rigorous techniques. The overarching goal is to provide a LiDAR system calibration that does not require raw measurements which can be carried out with minimal control and flight lines to reduce costs. This testing is unique because the terrain used for calibration does not contain gable roofs, all other LiDAR system calibration testing and development has been done with terrain containing features with high geometric integrity such as gable roofs.

scholarly journals KINEMATIC CALIBRATION USING LOW-COST LiDAR SYSTEM FOR MAPPING AND AUTONOMOUS DRIVING APPLICATIONS

2018 ◽  
Vol XLII-1 ◽  
pp. 445-450
Author(s):  
G. J. Tsai ◽  
K. W. Chiang ◽  
N. El-Sheimy
Keyword(s):  
Laser Scanning ◽  
Low Cost ◽  
Point Clouds ◽  
Autonomous Driving ◽  
Calibration Model ◽  
Kinematic Calibration ◽  
Lidar System ◽  
Calibration Process ◽  
Lever Arm ◽  
Calibration Parameters

<p><strong>Abstract.</strong> More recently, mapping sensors for land-based Mobile Mapping Systems (MMSs) have combined cameras and laser scanning measurements defined as Light Detection and Ranging (LiDAR), or laser scanner together. These mobile laser scanning systems (MLS) can be used in dynamic environments and are able of being adopted in traffic-related applications, such as the collection of road network databases, inventory of traffic sign and surface conditions, etc. However, most LiDAR systems are expensive and not easy to access. Moreover, due to the increasing demand of the autonomous driving system, the low-cost LiDAR systems, such as Velodyne or SICK, have become more and more popular these days. These kinds of systems do not provide the total solution. Users need to integrate with Inertial Navigation System/ Global Navigation Satellite System (INS/GNSS) or camera by themselves to meet their requirement. The transformation between LiDAR and INS frames must be carefully computed ahead of conducting direct geo-referencing. To solve these issues, this research proposes the kinematic calibration model for a land-based INS/GNSS/LiDAR system. The calibration model is derived from the direct geo-referencing model and based on the conditioning of target points where lie on planar surfaces. The calibration parameters include the boresight and lever arm as well as the plane coefficients. The proposed calibration model takes into account the plane coefficients, laser and INS/GNSS observations, and boresight and lever arm. The fundamental idea is the constraint where geo-referenced point clouds should lie on the same plane through different directions during the calibration. After the calibration process, there are two evaluations using the calibration parameters to enhance the performance of proposed applications. The first evaluation focuses on the direct geo-referencing. We compared the target planes composed of geo- referenced points before and after the calibration. The second evaluation concentrates on positioning improvement after taking aiding measurements from LiDAR- Simultaneously Localization and Mapping (SLAM) into INS/GNSS. It is worth mentioning that only one or two planes need to be adopted during the calibration process and there is no extra arrangement to set up the calibration field. The only requirement for calibration is the open sky area with the clear plane construction, such as wall or building. Not only has the contribution in MMSs or mapping, this research also considers the self-driving applications which improves the positioning ability and stability.</p>

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