Academic Journal

Tight Integration of GNSS and Static Level for High Accuracy Dilapidated House Deformation Monitoring.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Tight Integration of GNSS and Static Level for High Accuracy Dilapidated House Deformation Monitoring.
Συγγραφείς: Yang, Jian, Tang, Weiming, Xuan, Wei, Xi, Ruijie
Πηγή: Remote Sensing; Jun2022, Vol. 14 Issue 12, pN.PAG-N.PAG, 16p
Θεματικοί όροι: Global Positioning System
Περίληψη: Global Navigation Satellite System (GNSS) can provide high-precision three-dimensional real-time or quasi-real-time changes of monitoring points automatically in house monitoring applications. However, due to the signal sheltering problem, large observation noise and multipath effects in urban observing environment with dense buildings, ambiguity resolution would be hard, and GNSS accuracy cannot always achieve millimeter level to satisfy the requirement of house monitoring. Static level is a precision instrument for measuring elevation difference and its variations, with a precision up to sub-millimeter level. It could be integrated with GNSS to improve the positioning accuracy in height direction. However, the existing integration of GNSS and static level is mostly on a respective results level. In this study, we proposed a method of integrating GNSS and static level observations tightly to enhance the GNSS positioning performance. The hardware design and integration mathematic model in data processing were introduced, and a group of experiments were carried out to verify the performance in positioning with and without the static level observation constraints. It found that the vertical monitoring measurement results of static level can achieve less than 1 mm. The GNSS ambiguity resolution performance can be improved by incorporating the measurement of static level into GNSS positioning equation as external constraints, and the precision of GNSS float solutions was significantly improved. Finally, the static level constraint can further improve the accuracy of the fixed solution from about 2 cm to better than 2 mm in vertical direction, which is even better than the accuracy in horizontal directions with about 3–6 mm with the static level constraint. The tight combination data processing algorithm can significantly improve the working efficiency, accuracy, and reliability of the application of dangerous house monitoring. [ABSTRACT FROM AUTHOR]
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Βάση Δεδομένων: Complementary Index
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  Data: Tight Integration of GNSS and Static Level for High Accuracy Dilapidated House Deformation Monitoring.
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  Data: <searchLink fieldCode="AR" term="%22Yang%2C+Jian%22">Yang, Jian</searchLink><br /><searchLink fieldCode="AR" term="%22Tang%2C+Weiming%22">Tang, Weiming</searchLink><br /><searchLink fieldCode="AR" term="%22Xuan%2C+Wei%22">Xuan, Wei</searchLink><br /><searchLink fieldCode="AR" term="%22Xi%2C+Ruijie%22">Xi, Ruijie</searchLink>
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  Data: Remote Sensing; Jun2022, Vol. 14 Issue 12, pN.PAG-N.PAG, 16p
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  Data: <searchLink fieldCode="DE" term="%22Global+Positioning+System%22">Global Positioning System</searchLink>
– Name: Abstract
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  Data: Global Navigation Satellite System (GNSS) can provide high-precision three-dimensional real-time or quasi-real-time changes of monitoring points automatically in house monitoring applications. However, due to the signal sheltering problem, large observation noise and multipath effects in urban observing environment with dense buildings, ambiguity resolution would be hard, and GNSS accuracy cannot always achieve millimeter level to satisfy the requirement of house monitoring. Static level is a precision instrument for measuring elevation difference and its variations, with a precision up to sub-millimeter level. It could be integrated with GNSS to improve the positioning accuracy in height direction. However, the existing integration of GNSS and static level is mostly on a respective results level. In this study, we proposed a method of integrating GNSS and static level observations tightly to enhance the GNSS positioning performance. The hardware design and integration mathematic model in data processing were introduced, and a group of experiments were carried out to verify the performance in positioning with and without the static level observation constraints. It found that the vertical monitoring measurement results of static level can achieve less than 1 mm. The GNSS ambiguity resolution performance can be improved by incorporating the measurement of static level into GNSS positioning equation as external constraints, and the precision of GNSS float solutions was significantly improved. Finally, the static level constraint can further improve the accuracy of the fixed solution from about 2 cm to better than 2 mm in vertical direction, which is even better than the accuracy in horizontal directions with about 3–6 mm with the static level constraint. The tight combination data processing algorithm can significantly improve the working efficiency, accuracy, and reliability of the application of dangerous house monitoring. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.3390/rs14122943
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 16
        StartPage: N.PAG
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      – SubjectFull: Global Positioning System
        Type: general
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      – TitleFull: Tight Integration of GNSS and Static Level for High Accuracy Dilapidated House Deformation Monitoring.
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            NameFull: Yang, Jian
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            NameFull: Tang, Weiming
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            NameFull: Xuan, Wei
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            – D: 15
              M: 06
              Text: Jun2022
              Type: published
              Y: 2022
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              Value: 12
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