A unified approach to self-calibration of terrestrial laser scanners

In recent years, the method of self-calibration widely used in photogrammetry has been found suitable for the estimation of systematic errors in terrestrial laser scanners. Since high correlations can be present between the estimated parameters, ways to reduce them have to be found. This paper presents a unified approach to self-calibration of terrestrial laser scanners, where the parameters in a least-squares adjustment are treated as observations by assigning appropriate weights to them. The higher these weights are the lower the parameter correlations are expected to be. Self-calibration of a pulsed laser scanner Leica Scan Station was performed with the unified approach. The scanner position and orientation were determined during the measurements with the help of a total station, and the point clouds were directly georeferenced. The significant systematic errors were zero error in the laser rangefinder and vertical circle index error. Most parameter correlations were comparatively low. In part, precise knowledge of the horizontal coordinates of the scanner centre helped greatly to achieve low correlation between these parameters and the zero error. The approach was shown to be advantageous to the use of adjustment with stochastic (weighted) inner constraints where the parameter correlations were higher. At the same time, the collimation error could not be estimated reliably due to its high correlation with the scanner azimuth because of a limited vertical distribution of the targets in the calibration field. While this problem can be solved for a scanner with a nearly spherical field-of-view, it will complicate the calibration of scanners with limited vertical field-of-view. Investigations into the influence of precision of the scanner position and levelling on the adjustment results lead to two important findings. First, it is not necessary to level the scanner during the measurements when using the unified approach since the parameter correlations are relatively low anyway. Second, the scanner position has to be known with a precision of about 1 mm in order to get a reliable estimate of the zero error.     

Error modelling,calibration and analysis of an AM–CW terrestrial laser scanner system

A rigorous method for terrestrial laser scanner self-calibration using a network of signalised points is presented. Exterior orientation, object point co-ordinates and additional parameters are estimated simultaneously by free network adjustment. Spherical co-ordinate observation equations are augmented with a set of additional parameters that model systematic errors in range, horizontal direction and elevation angle. The error models include both physically interpretable and empirically identified components. Though the focus is on one particular make and model of AM–CW scanner system, the Faro 880, the mathematical models are formulated in a general framework so their application to other instruments only requires selection of an appropriate set of additional parameters. Results from controlled testing show that significant improvement is achieved by using the proposed model in terms of both reducing the magnitude of observational residuals as well as the three-dimensional positioning accuracy of signalised points. Ten self-calibration datasets captured over the course of 13 months are used to examine short- and long-term additional parameter stability via standard hypothesis testing techniques. Detailed investigations into correlation mechanisms between model parameters accompany the self-calibration solution analyses. Other contributions include an observation model for incorporation of integrated inclinometer observations into the self-calibration solution and an effective a priori outlier removal method. The benefit of the former is demonstrated to be reduced correlation between exterior orientation and additional parameters, even if inclinometer precision is low. The latter is arrived at by detailed analysis of the influence of incidence angle on range.     

Parameter de-correlation and model-identification in hybrid-style terrestrial laser scanner self-calibration

One of the important systematic error parameters identified in terrestrial laser scanners is the collimation axis error, which models the non-orthogonality between two instrumental axes. The quality of this parameter determined by self-calibration, as measured by its estimated precision and its correlation with the tertiary rotation angle κ of the scanner exterior orientation, is strongly dependent on instrument architecture. While the quality is generally very high for panoramic-type scanners, it is comparably poor for hybrid-style instruments. Two methods for improving the quality of the collimation axis error in hybrid instrument self-calibration are proposed herein: (1) the inclusion of independent observations of the tertiary rotation angle κ; and (2) the use of a new collimation axis error model. Five real datasets were captured with two different hybrid-style scanners to test each method’s efficacy. While the first method achieves the desired outcome of complete decoupling of the collimation axis error from κ, it is shown that the high correlation is simply transferred to other model variables. The second method achieves partial parameter de-correlation to acceptable levels. Importantly, it does so without any adverse, secondary correlations and is therefore the method recommended for future use. Finally, systematic error model identification has been greatly aided in previous studies by graphical analyses of self-calibration residuals. This paper presents results showing the architecture dependence of this technique, revealing its limitations for hybrid scanners.     

Geometric calibration of a terrestrial laser scanner with local additional parameters: An automatic strategy

Terrestrial laser scanning systems are steadily increasing in many fields of engineering, geoscience and architecture namely for fast data acquisition, 3-D modeling and mapping. Similarly to other precision instruments, these systems provide measurements with implicit systematic errors. Systematic errors are physically corrected by manufacturers before delivery and sporadically afterwards. The approach presented herein tackles the raw observables acquired by a laser scanner with additional parameters, a set of geometric calibration parameters that model the systematic error of the instrument to achieve the most accurate point cloud outputs, improving eventual workflow owing to less filtering, better registration and best 3D modeling. This paper presents a fully automatic strategy to calibrate geometrically terrestrial laser scanning datasets. The strategy is tested with multiple scans taken by a FARO FOCUS 3D, a phase-based terrestrial laser scanner. A calibration with local parameters for datasets is undertaken to improve the raw observables and a weighted mathematical index is proposed to select the most significant set of additional parameters. The improvements achieved are exposed, highlighting the necessity of correcting the terrestrial laser scanner before handling multiple data sets.     

An integrated bundle adjustment approach to range camera geometric self-calibration

This paper describes a new method for integrated range camera system self-calibration in which both traditional camera calibration parameters and rangefinder systematic error parameters are estimated simultaneously in a free-network bundle adjustment of observations to signalised targets. Its mathematical basis is collinearity and range observation equations augmented with correction models for systematic error sources identified in the data. The self-calibration results from datasets captured with two different range cameras, a SwissRanger SR3000 and a SwissRanger SR4000, are presented and analysed in detail. The method’s effectiveness is demonstrated in terms of systematic error removal and independent accuracy assessment. Up to a 54% reduction in the residual RMS was achieved by inclusion of the proposed error models in the self-calibration adjustment. An improvement of at least 74% in the RMS of object point co-ordinate differences, over that achieved without calibration or provided by the manufacturer’s software (in the case of the SR3000), was realised in an independent accuracy assessment. In addition, the effects of several influencing variables, including the range stochastic error model, the network geometry and the range measurements themselves, on key correlation mechanisms are analysed in detail.     

Scanning geometry: Influencing factor on the quality of terrestrial laser scanning points

A terrestrial laser scanner measures the distance to an object surface with a precision in the order of millimeters. The quality of the individual points in a point cloud, although directly affecting standard processing steps like point cloud registration and segmentation, is still not well understood. The quality of a scan point is influenced by four major factors: instrument mechanism, atmospheric conditions, object surface properties and scan geometry. In this paper, the influence of the scan geometry on the individual point precision or local measurement noise is considered. The local scan geometry depends on the distance and the orientation of the scanned surface, relative to the position of the scanner. The local scan geometry is parameterized by two main parameters, the range, i.e. the distance from the object to the scanner and the incidence angle, i.e. the angle between incoming laser beam and the local surface normal. In this paper, it is shown that by studying the influence of the local scan geometry on the signal to noise ratio, the dependence of the measurement noise on range and incidence angle can be successfully modeled if planar surfaces are observed. The implications of this model is demonstrated further by comparing two point clouds of a small room, obtained from two different scanner positions: a center position and a corner position. The influence of incidence angle on the noise level is quantified on scans of this room, and by moving the scanner by 2 m, it is reduced by 20%. The improvement of the standard deviation is significant, going from 3.23 to 2.55 mm. It is possible to optimize measurement setups in such a way that the measurement noise due to bad scanning geometry is minimized and therefore contribute to a more efficient acquisition of point clouds of better quality.     

地面三维激光扫描仪测距检校与精度评定

作为一项新的数据获取技术,地面三维激光扫描技术正被越来越多地应用于多个领域,同时也对该技术测量精度提出了更高的要求。本文根据六段解析模型设计合理有效的试验过程,拟对徕卡C10三维激光扫描仪的测距检校与精度进行评定,为提高今后地面三维激光扫描仪测量精度提供参考。     

三维激光扫描仪在特殊地貌测量中的应用研究

三维激光扫描仪作为一种非接触数据采集设备,在特殊地貌的大比例尺地形测绘中有着广泛的应用前景。本文以草原石城景区为例,阐述了三维激光扫描仪在这种特殊地貌测绘中的应用原理,数据拼接和配准的方法,并与全站仪全野外数字采集的成果进行了高程和平面坐标的比对,证明了使用三维激光扫描仪测绘特殊地貌精度高、速度快,地貌表达逼真,为特殊地貌区域的大比例尺地形图测绘提供了新的技术手段。     

地面3维激光扫描仪测量精度试验与分析

地面3维激光扫描仪是一种可进行全自动高精度立体扫描的先进仪器。其特点是可大面积高分辨率地快速获取被测对象表面的3维坐标数据,且所获取的数据具有实时、动态、高密度、高精度等优点。因而,激光扫描测量仪器的精度对工程应用的影响以及对3维点云模型的建立和精度影响至关重要。文章针对瑞格公司所生产的VZ400扫描仪在测量时,距离、入射角度、目标颜色几个因素对精度产生的影响进行研究。利用平面拟合的方法分析精度,得出了随着距离的增加,入射角的增大,会导致地面3维激光扫描仪测量精度降低的定性分析结论．     

基于自检校的机载线阵CCD传感器几何标定

将基于附加参数的自检校光束法区域网平差技术应用于机载线阵CCD传感器几何标定中,以ADS40为对象,分析集成传感器成像几何关系,引入GPS观测值数学模型和IMU视轴偏心角模型,建立用于标定的自检校光束法区域网平差模型;在深入分析机载三线阵CCD传感器成像误差特性的基础上,建立有效的相机标定参数模型;并采用检校场ADS40数据进行了标定试验,结果表明几何标定方法可行有效,可显著提高测量精度和可靠性。     

基于地面三维激光扫描仪点云数据的去噪算法研究

原始三维激光点云数据中存在由于仪器本身、外界环境、实体表面特征等因素导致的噪点,严重影响点云质量以及后处理效果。针对地面三维激光扫描仪原始激光点云数据的去噪问题,本文进行了3种有序点云去噪算法的研究,并采用VC++编程语言进行算法的功能实现,最后选取某区域单站地面原始三维激光点云数据进行实验分析,总结了各算法的优缺点及适用条件。     

天宝GX200地面三维激光扫描仪鉴别率检定

三维激光扫描技术是一种新兴的全自动、高精度测量技术。三维激光扫描仪能够在短时间内大面积、高密度地获取目标的空间点云数据,逼真细腻地描述目标表面。三维激光扫描仪作为一种测量仪器,本身也存在误差。目前,我国三维激光扫描仪检定技术较为薄弱且尚未制定系统的技术规范。本文结合国内外对三维激光扫描仪性能检定的理论方法,设计相应的实验方案,对所用Trimble GX200扫描仪的鉴别率进行检定。     

车载3D激光扫描系统集成技术

移动激光扫描技术是从上世纪90年代初逐步发展起来的一门测绘技术,也是当今测绘界最为前沿的技术之一,可用于工程测量和制图等诸多领域。地面3D激光扫描仪具有测量速度快,精度高等优点。本文以奥地利RIEGL公司的地面三维激光扫描仪VZ400为例,研究将其作为移动测量系统的主要传感器所涉及的关键技术,包括联机控制、时间基准统一和空间基准统一三个方面:解析了激光扫描仪的接口定义,并结合联机控制的开发库——RiVLIB实现的仪器的联机控与数据通信;给出了基于GPS秒脉冲信号的时间同步原理,实现了系统时间基准的传递与统一;分析了移动测量系统中的坐标系,并根据地面三维激光扫描仪的实际情况,构建了单站的参数标定模型。通过本文的研究与实验,使测量系统实现常见移动测量的二维帧扫描模式以及针对重点区域的三维全景扫描模式,同时,当它闲置时还可将激光扫描仪拆卸进行静态的扫描,丰富了系统的测量方式,提高了系统的适应性与使用效率。     

地面三维激光扫描仪系统误差标定

介绍了地面三维激光扫描仪工作原理,采用自检校法对仪器系统误差进行标定并详细推导了自检校系统误差模型。利用徕卡HDS3000获取的数据进行分析计算,得到该仪器的系统误差值,同时对获取的数据进行改正,并通过检验点验证系统误差改正效果。实验表明,经过系统误差改正后,HDS3000扫描仪的测量准确度可以提高一倍,效果良好。     

亚热带森林参数的机载激光雷达估测

通过应用机载激光雷达数据,在分析云南省中部的78块样地的基础上提出2个预测森林不同生物特性的统计模型(加权平均高度的预测模型和生物量的预测模型),并讨论了预测结果及其精确性。从激光雷达数据中提取了2组变量(树冠高度变量组和植被密度变量组)作为自变量,采用逐步回归方法进行自变量选择。结果表明,激光雷达数据与森林的平均树高和地上各部分生物量有很强的相关性。对于3种不同森林类型(针叶林,阔叶林和混交林),平均树高估测均能达到比较高的精度;生物量的估测结果是针叶林优于阔叶林,混交林的生物量与激光雷达数据则没有明显相关性。最后,对回归分析的结果和影响预测精度的因素进行讨论,认为预测结果的精度可能与森林类型、激光雷达采样时间和采样密度以及坐标误差等因素有关。     

Sensor modeling,self-calibration and accuracy testing of panoramic cameras and laser scanners

Terrestrial Linear Array CCD-based panoramic cameras have been used for purely imaging purposes, but they also have a high potential for use in high accuracy measurement applications. The imaging geometry and the high information content of those images make them suitable candidates for quantitative image analysis. For that a particular sensor model has to be established and the inherent accuracy potential has to be investigated. We developed a sensor model for terrestrial Linear Array-based panoramic cameras by means of a modified bundle adjustment with additional parameters, which models substantial deviations of a real camera from the ideal one. We used 3D straight-line information in addition to tie points to conduct a full calibration and orientation without control point information. Due to the similarity of the operation of laser scanners to panoramic cameras the sensor model of the panoramic cameras was extended for the self-calibration of laser scanners. We present the joint sensor model for panoramic cameras and laser scanners and the results of self-calibration, which indicate a subpixel accuracy level for such highly dynamic systems. Finally we demonstrate the systems’ accuracy of two typical panoramic cameras in 3D point positioning, using both a minimal number of control points and a free network adjustment. With these new panoramic imaging devices we have additional powerful sensors for image recording and efficient 3D object modeling.     

机载三线阵CCD影像自检校光束法区域网平差

将基于附加参数的自检校光束法区域网平差技术应用于机载三线阵CCD传感器ADS40影像的几何定位处理,分析了机载三线阵CCD传感器成像的误差特性,建立了相适有效的自检校附加参数模型,以及3种形式的外方位元素变化模型和自检校光束法区域网平差模型。实验结果表明,自检校光束法区域网平差能够有效补偿ADS40影像存在的系统误差,显著提高定位精度。     

机载三线阵传感器ADS40的几何检校

ADS40为集成POS系统的机载三线阵数字航摄仪.分析ADS40相机独特的POS系统辅助传感器几何关系,介绍基于BROWN模型的利用附加参数的自检校法,设计针对ADS40的相机检校方案,包括:判断几何检校的必要性,进行几何检校,以及验证几何检校成果的有效性.试验结果证明,对ADS40进行相机几何检校可以有效提高数据的精...     

ALOS PRISM自检校光束法区域网平差

针对ALOS PRISM三线阵传感器,综合镜头光学畸变、像元尺寸和主距变化等影响,构建内定向参数模型;同时利用多项武模型,描述影像的外方位元素变化特征,建立自检校光束法区域网平差模型.利用ALOSPRISM实际数据对内定向参数模型进行研究和优化.结果表明,合适的内定向参数模型能起到良好的定标效果.     

地面几何标定的定向片自检校光束法区域网平差模型

针对航天线阵传感器,综合镜头光学畸变影响、像元尺寸与焦距的变化影响以及镜头的旋转作用,构建8标定参数的内方位自检校模型;利用定向片内插模型,描述影像的外方位元素变化;建立自检校光束法区域网平差模型,在对模型进行线性化的过程中,引入待标定的定向片外方位元素;利用SPOT5模拟数据对平差模型进行实验验证,结果表明,平差模型能够联合标定内方位自检校参数与外方位元素,标定结果准确。