A Refined Multipath Correction Model for High-Precision GNSS Deformation Monitoring
In deformation monitoring, the severe GNSS multipath caused by reflective surfaces can significantly degrade positioning accuracy. However, traditional multipath mitigation methods often assume strong day-to-day repeatability of residual errors, which is not always valid in complex monitoring enviro...
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MDPI AG
2025-08-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/15/2694 |
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| author | Yan Chen Ran Lu Xingyu Zhou Mingkun Su Mingyuan Zhang |
| author_facet | Yan Chen Ran Lu Xingyu Zhou Mingkun Su Mingyuan Zhang |
| author_sort | Yan Chen |
| collection | DOAJ |
| description | In deformation monitoring, the severe GNSS multipath caused by reflective surfaces can significantly degrade positioning accuracy. However, traditional multipath mitigation methods often assume strong day-to-day repeatability of residual errors, which is not always valid in complex monitoring environments. We propose a novel GNSS multipath correction approach that leverages multi-day post-fit residual data and principal component analysis to extract stable multipath signals, integrating them into an enhanced spatial repeatability multipath correction model. This method can effectively isolate true multipath errors, even under conditions of weak inter-day repeatability. Experimental results from a dam monitoring network demonstrate that the proposed method reduces the root mean square (RMS) error of single-day kinematic positioning by about 1.8 mm, 2.4 mm, and 6.7 mm in the East, North, and Up components, respectively. For static positioning solutions over 1 h, 2 h, and 4 h sessions, the RMS in East, North, and Up is reduced by approximately 40% on average. After correction, 2 h sessions achieve ~1.1 mm horizontal and ~3.0 mm vertical accuracy, while 4 h sessions reach ~0.9 mm horizontal and ~2.5 mm vertical accuracy. These improvements confirm that the proposed method effectively mitigates multipath effects and meets the high-precision requirements of deformation monitoring. |
| format | Article |
| id | doaj-art-b5f5d289e118463aacfe7a2cf4bc7bd2 |
| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-b5f5d289e118463aacfe7a2cf4bc7bd22025-08-20T03:36:32ZengMDPI AGRemote Sensing2072-42922025-08-011715269410.3390/rs17152694A Refined Multipath Correction Model for High-Precision GNSS Deformation MonitoringYan Chen0Ran Lu1Xingyu Zhou2Mingkun Su3Mingyuan Zhang4School of Earth Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, ChinaGNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaGNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaSchool of Communication Engineering, Hangzhou Dianzi University, No.1158 Baiyang Road, Hangzhou 310018, ChinaInnovation Academy for Microsatellites of Chinese Academy of Sciences, No.1 Xueyang Road, Shanghai 200120, ChinaIn deformation monitoring, the severe GNSS multipath caused by reflective surfaces can significantly degrade positioning accuracy. However, traditional multipath mitigation methods often assume strong day-to-day repeatability of residual errors, which is not always valid in complex monitoring environments. We propose a novel GNSS multipath correction approach that leverages multi-day post-fit residual data and principal component analysis to extract stable multipath signals, integrating them into an enhanced spatial repeatability multipath correction model. This method can effectively isolate true multipath errors, even under conditions of weak inter-day repeatability. Experimental results from a dam monitoring network demonstrate that the proposed method reduces the root mean square (RMS) error of single-day kinematic positioning by about 1.8 mm, 2.4 mm, and 6.7 mm in the East, North, and Up components, respectively. For static positioning solutions over 1 h, 2 h, and 4 h sessions, the RMS in East, North, and Up is reduced by approximately 40% on average. After correction, 2 h sessions achieve ~1.1 mm horizontal and ~3.0 mm vertical accuracy, while 4 h sessions reach ~0.9 mm horizontal and ~2.5 mm vertical accuracy. These improvements confirm that the proposed method effectively mitigates multipath effects and meets the high-precision requirements of deformation monitoring.https://www.mdpi.com/2072-4292/17/15/2694GNSSmultipath errorT-MHMdeformation monitoring |
| spellingShingle | Yan Chen Ran Lu Xingyu Zhou Mingkun Su Mingyuan Zhang A Refined Multipath Correction Model for High-Precision GNSS Deformation Monitoring Remote Sensing GNSS multipath error T-MHM deformation monitoring |
| title | A Refined Multipath Correction Model for High-Precision GNSS Deformation Monitoring |
| title_full | A Refined Multipath Correction Model for High-Precision GNSS Deformation Monitoring |
| title_fullStr | A Refined Multipath Correction Model for High-Precision GNSS Deformation Monitoring |
| title_full_unstemmed | A Refined Multipath Correction Model for High-Precision GNSS Deformation Monitoring |
| title_short | A Refined Multipath Correction Model for High-Precision GNSS Deformation Monitoring |
| title_sort | refined multipath correction model for high precision gnss deformation monitoring |
| topic | GNSS multipath error T-MHM deformation monitoring |
| url | https://www.mdpi.com/2072-4292/17/15/2694 |
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