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The performance of the quadratic kinematic deformation analysis model
•The coordinated differences estimated by Bernese v5.2 are close to the true values.•Quadratic model is mostly preferred in Kinematic Deformation Analysis (KDA).•The Least Square Estimation smears the effects of the displacements to all points.•Smearing effect decrease the reliability of the quadrat...
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Published in: | Measurement : journal of the International Measurement Confederation 2020-05, Vol.156, p.107607, Article 107607 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | •The coordinated differences estimated by Bernese v5.2 are close to the true values.•Quadratic model is mostly preferred in Kinematic Deformation Analysis (KDA).•The Least Square Estimation smears the effects of the displacements to all points.•Smearing effect decrease the reliability of the quadratic KDA method.
Kinematic Deformation Analysis (KDA) models are preferred to estimate displacement, velocity and acceleration parameters. The quadratic models are often used in KDA. To estimate the reliability of the model, Linear Motion Systems (LMS) integrated with GPS were established at four object points located properly in University Campus. Moreover, five continuously operating GPS sites (off-campus) were predefined as reference points. The object points were displaced along three different planes: 1st Vertical direction (Up), 2nd Horizontal plane (Northeast) and 3rd Horizontal plane and vertical direction for intended scenarios as considering the different magnitudes for velocity and acceleration. Each deformation scenario contains four epochs of GPS observations with eight hours of session duration. According to the obtained results, the displacements estimated by the Bernese v5.2 scientific software are close to their real values. However, the quadratic KDA model spreads the effects of the displaced points to other nondisplaced points. |
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ISSN: | 0263-2241 1873-412X |
DOI: | 10.1016/j.measurement.2020.107607 |