A synthetic covariance matrix for monitoring by terrestrial laser scanning

Kauker, Stephanie; Schwieger, Volker

doi:10.1515/jag-2016-0026

Cited by 35 publications

(22 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Assessing the correlation structure of the TLS range with a general model is a complex task. An empirically-based method was proposed in Reference [36]: the residuals of a LS adjustment of a scanned plane were fitted by an exponential function. This function is known to have a substantial limitation in most geostatistical studies due to the small degree of smoothness of the covariance function [38].…”

Section: Case (Iii)mentioning

confidence: 99%

See 1 more Smart Citation

Deformation Analysis Using B-Spline Surface with Correlated Terrestrial Laser Scanner Observations—A Bridge Under Load

2020

View full text Add to dashboard Cite

The choice of an appropriate metric is mandatory to perform deformation analysis between two point clouds (PC)—the distance has to be trustworthy and, simultaneously, robust against measurement noise, which may be correlated and heteroscedastic. The Hausdorff distance (HD) or its averaged derivation (AHD) are widely used to compute local distances between two PC and are implemented in nearly all commercial software. Unfortunately, they are affected by measurement noise, particularly when correlations are present. In this contribution, we focus on terrestrial laser scanner (TLS) observations and assess the impact of neglecting correlations on the distance computation when a mathematical approximation is performed. The results of the simulations are extended to real observations from a bridge under load. Highly accurate laser tracker (LT) measurements were available for this experiment: they allow the comparison of the HD and AHD between two raw PC or between their mathematical approximations regarding reference values. Based on these results, we determine which distance is better suited in the case of heteroscedastic and correlated TLS observations for local deformation analysis. Finally, we set up a novel bootstrap testing procedure for this distance when the PC are approximated with B-spline surfaces.

show abstract

Section: Case (Iii)mentioning

confidence: 99%

“…In a first step, we will simulate the PC of TLS raw observations in polar co-ordinates. They are known to be both heteroscedastic ( [12,35]) and correlated ( [15,36]). Thus, we will extend the stochastic model of TLS measurements using a separable covariance function to simulate correlated range observations ( [37,38]).…”

Section: Introductionmentioning

confidence: 99%

Deformation Analysis Using B-Spline Surface with Correlated Terrestrial Laser Scanner Observations—A Bridge Under Load

2020

View full text Add to dashboard Cite

show abstract

“…Later on, the model was elegantly presented by Pelzer [21] and extended by Schwieger [31]. Some of its applications can be found in exemplifying the error impact on several geodetic measurement methods like electronic distance measurement (EDM) instruments [32], GNSS observations [33] or recently TLS measurements [17].…”

Section: Elementary Error Theorymentioning

confidence: 99%

“…To overcome this issue, the Elementary Error Model (EEM) can be used to define the stochastic model of TLS observations in form of a VCM that considers correlations. Previous work of Kauker and Schwieger [17] sets the foundation of applying the EEM on TLS measurements. To that point, the EEM model was applied on a TLS of panoramic type [9] and the atmospheric elementary errors were considered functional correlating.…”

Section: Introductionmentioning

confidence: 99%

Elementary Error Model Applied to Terrestrial Laser Scanning Measurements: Study Case Arch Dam Kops

Kerekes

Schwieger

2020

Mathematics

Self Cite

View full text Add to dashboard Cite

All measurements are affected by systematic and random deviations. A huge challenge is to correctly consider these effects on the results. Terrestrial laser scanners deliver point clouds that usually precede surface modeling. Therefore, stochastic information of the measured points directly influences the modeled surface quality. The elementary error model (EEM) is one method used to determine error sources impact on variances-covariance matrices (VCM). This approach assumes linear models and normal distributed deviations, despite the non-linear nature of the observations. It has been proven that in 90% of the cases, linearity can be assumed. In previous publications on the topic, EEM results were shown on simulated data sets while focusing on panorama laser scanners. Within this paper an application of the EEM is presented on a real object and a functional model is introduced for hybrid laser scanners. The focus is set on instrumental and atmospheric error sources. A different approach is used to classify the atmospheric parameters as stochastic correlating elementary errors, thus expanding the currently available EEM. Former approaches considered atmospheric parameters functional correlating elementary errors. Results highlight existing spatial correlations for varying scanner positions and different atmospheric conditions at the arch dam Kops in Austria.

show abstract

“…external influences or atmospheric conditions (temperature, air pressure, etc.) [1]; • properties of the captured object (color, material, shape) [2,3]; • sensor-internal influences (axis error, tumbling error, linearity deviation) [4][5][6]; • measurement set-up (distance, angle of incidence horizontal and vertical) [1,7,8]; • (geo-) referencing including stationing and registration (referencing means framing in a local and geo-referencing in a global reference frame, (geo-) referencing implies that both is possible).…”

mentioning

confidence: 99%

High-Precision 3D Object Capturing with Static and Kinematic Terrestrial Laser Scanning in Industrial Applications—Approaches of Quality Assessment

Stenz¹,

Hartmann

Paffenholz

et al. 2020

Remote Sensing

View full text Add to dashboard Cite

Terrestrial laser scanning is used in many disciplines of engineering. Examples include mobile mapping, architecture surveying, archaeology, as well as monitoring and surveillance measurements. For most of the mentioned applications, 3D object capturing in an accuracy range of several millimeters up to a few centimeters is sufficient. However, in engineering geodesy, particularly in industrial surveying or monitoring measurements, accuracies in a range of a few millimeters are required. Additional increased quality requirements apply to these applications. This paper focuses on the quality investigation of data captured with static and kinematic terrestrial laser scanning. For this purpose, suitable sensors, which are typically used in the approach of a multi-sensor-system, as well as the corresponding data capturing/acquisition strategies, are presented. The aim of such systems is a geometry- and surface-based analysis in an industrial environment with an accuracy of +/− 1–2 mm or better.

show abstract

A synthetic covariance matrix for monitoring by terrestrial laser scanning

Cited by 35 publications

References 11 publications

Deformation Analysis Using B-Spline Surface with Correlated Terrestrial Laser Scanner Observations—A Bridge Under Load

Deformation Analysis Using B-Spline Surface with Correlated Terrestrial Laser Scanner Observations—A Bridge Under Load

Elementary Error Model Applied to Terrestrial Laser Scanning Measurements: Study Case Arch Dam Kops

High-Precision 3D Object Capturing with Static and Kinematic Terrestrial Laser Scanning in Industrial Applications—Approaches of Quality Assessment

Contact Info

Product

Resources

About