Rapid Deformation Identification and Adaptive Filtering with GNSS TDCP Under Different Scenarios and Its Application in Landslide Monitoring
Global navigation satellite system (GNSS) real-time kinematic (RTK) has been widely applied in landslide monitoring and warning, since it can provide real-time and high-precision three-dimensional deformation information in all weather and all the time. The Kalman filter is often adopted for paramet...
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MDPI AG
2025-05-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/10/1751 |
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| _version_ | 1849327120021454848 |
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| author | Mingkui Wu Rui Wen Yue Zhang Wanke Liu |
| author_facet | Mingkui Wu Rui Wen Yue Zhang Wanke Liu |
| author_sort | Mingkui Wu |
| collection | DOAJ |
| description | Global navigation satellite system (GNSS) real-time kinematic (RTK) has been widely applied in landslide monitoring and warning, since it can provide real-time and high-precision three-dimensional deformation information in all weather and all the time. The Kalman filter is often adopted for parameter estimation in GNSS RTK positioning since it can effectively suppress the observational noise and improve the positioning accuracy and reliability. However, the discrepancy between the empirical state model in the Kalman filter and the actual state of the monitoring object could lead to large positioning errors or even the divergence of the Kalman filter. In this contribution, we propose a novel rapid deformation identification and adaptive filtering approach with GNSS time-differenced carrier phase (TDCP) under different scenarios for landslide monitoring. We first present the methodology of the proposed TDCP-based rapid deformation identification and adaptive filtering approach for GNSS RTK positioning. The effectiveness of the proposed approach is then validated with a simulated displacement experiment with a customized three-dimensional displacement platform. The experimental results demonstrate that the proposed approach can accurately and promptly identify the rapid between-epoch deformation of more than approximately 1.5 cm and 3.0 cm for the horizontal and vertical components for the monitoring object under a complex observational environment. Meanwhile, it can effectively suppress the observational noise and thus maintain mm-to-cm-level monitoring accuracy. The proposed approach can provide high-precision and reliable three-dimensional deformation information for GNSS landslide monitoring and early warning. |
| format | Article |
| id | doaj-art-aa4ffd62df3349c3a0ca3da28aaa82d8 |
| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-aa4ffd62df3349c3a0ca3da28aaa82d82025-08-20T03:47:58ZengMDPI AGRemote Sensing2072-42922025-05-011710175110.3390/rs17101751Rapid Deformation Identification and Adaptive Filtering with GNSS TDCP Under Different Scenarios and Its Application in Landslide MonitoringMingkui Wu0Rui Wen1Yue Zhang2Wanke Liu3School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan 430074, ChinaSchool of Geodesy and Geomatics, Wuhan University, Wuhan 430079, ChinaSchool of Geodesy and Geomatics, Wuhan University, Wuhan 430079, ChinaSchool of Geodesy and Geomatics, Wuhan University, Wuhan 430079, ChinaGlobal navigation satellite system (GNSS) real-time kinematic (RTK) has been widely applied in landslide monitoring and warning, since it can provide real-time and high-precision three-dimensional deformation information in all weather and all the time. The Kalman filter is often adopted for parameter estimation in GNSS RTK positioning since it can effectively suppress the observational noise and improve the positioning accuracy and reliability. However, the discrepancy between the empirical state model in the Kalman filter and the actual state of the monitoring object could lead to large positioning errors or even the divergence of the Kalman filter. In this contribution, we propose a novel rapid deformation identification and adaptive filtering approach with GNSS time-differenced carrier phase (TDCP) under different scenarios for landslide monitoring. We first present the methodology of the proposed TDCP-based rapid deformation identification and adaptive filtering approach for GNSS RTK positioning. The effectiveness of the proposed approach is then validated with a simulated displacement experiment with a customized three-dimensional displacement platform. The experimental results demonstrate that the proposed approach can accurately and promptly identify the rapid between-epoch deformation of more than approximately 1.5 cm and 3.0 cm for the horizontal and vertical components for the monitoring object under a complex observational environment. Meanwhile, it can effectively suppress the observational noise and thus maintain mm-to-cm-level monitoring accuracy. The proposed approach can provide high-precision and reliable three-dimensional deformation information for GNSS landslide monitoring and early warning.https://www.mdpi.com/2072-4292/17/10/1751global navigation satellite system (GNSS)landslide monitoringreal-time kinematic (RTK)time-differenced carrier phase (TDCP)Kalman filter |
| spellingShingle | Mingkui Wu Rui Wen Yue Zhang Wanke Liu Rapid Deformation Identification and Adaptive Filtering with GNSS TDCP Under Different Scenarios and Its Application in Landslide Monitoring Remote Sensing global navigation satellite system (GNSS) landslide monitoring real-time kinematic (RTK) time-differenced carrier phase (TDCP) Kalman filter |
| title | Rapid Deformation Identification and Adaptive Filtering with GNSS TDCP Under Different Scenarios and Its Application in Landslide Monitoring |
| title_full | Rapid Deformation Identification and Adaptive Filtering with GNSS TDCP Under Different Scenarios and Its Application in Landslide Monitoring |
| title_fullStr | Rapid Deformation Identification and Adaptive Filtering with GNSS TDCP Under Different Scenarios and Its Application in Landslide Monitoring |
| title_full_unstemmed | Rapid Deformation Identification and Adaptive Filtering with GNSS TDCP Under Different Scenarios and Its Application in Landslide Monitoring |
| title_short | Rapid Deformation Identification and Adaptive Filtering with GNSS TDCP Under Different Scenarios and Its Application in Landslide Monitoring |
| title_sort | rapid deformation identification and adaptive filtering with gnss tdcp under different scenarios and its application in landslide monitoring |
| topic | global navigation satellite system (GNSS) landslide monitoring real-time kinematic (RTK) time-differenced carrier phase (TDCP) Kalman filter |
| url | https://www.mdpi.com/2072-4292/17/10/1751 |
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