SNR-Dependent Environmental Model: Application in Real-Time GNSS Landslide Monitoring
1
National Time Service Center, Chinese Academy of Sciences, Shu Yuan Road, Xi’an 710600, China
2
Key Laboratory of Time and Frequency Primary Standards, Chinese Academy of Sciences, Xi’an 710600, China
3
College of Electronic, Electrical and Communication Engineering, Chinese Academy of Sciences, Yu Quan Road, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(22), 5017; https://doi.org/10.3390/s19225017
Received: 16 September 2019
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Revised: 14 November 2019
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Accepted: 14 November 2019
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Published: 17 November 2019
(This article belongs to the Collection Positioning and Navigation (Closed))
The Global Navigation Satellite System (GNSS) is currently one of the important tools for landslide monitoring and early warning. However, the majority of GNSS devices are installed in mountainous areas and a variety of vegetation. These harsh environments lead to defective signals at high elevation angles, rendering real-time successive and reliable positioning results for monitoring difficult. In this study, an environmental model derived from signal-to-noise ratio (SNR) is proposed to enhance the precision and convergence time of positioning in harsh environments. A series of experiments are conducted on weighting and ambiguity-fixed models to evaluate performance. The results indicate that the proposed SNR-dependent environment model could lead to a significant improvement in precision and convergence time; with an obtained root mean squared result on the millimeter level, a convergence time of a few seconds, and utilization which could reach 100%, for continuous and reliable positioning results. These results indicate that the proposed SNR-dependent environment model enhances the performance of GNSS monitoring and early warning to provide continuous and reliable positioning results in real-time.
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Keywords:
GNSS; SNR-dependent; environment model; landslide monitoring
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MDPI and ACS Style
Han, J.; Tu, R.; Zhang, R.; Fan, L.; Zhang, P. SNR-Dependent Environmental Model: Application in Real-Time GNSS Landslide Monitoring. Sensors 2019, 19, 5017. https://doi.org/10.3390/s19225017
AMA Style
Han J, Tu R, Zhang R, Fan L, Zhang P. SNR-Dependent Environmental Model: Application in Real-Time GNSS Landslide Monitoring. Sensors. 2019; 19(22):5017. https://doi.org/10.3390/s19225017
Chicago/Turabian StyleHan, Junqiang, Rui Tu, Rui Zhang, Lihong Fan, and Pengfei Zhang. 2019. "SNR-Dependent Environmental Model: Application in Real-Time GNSS Landslide Monitoring" Sensors 19, no. 22: 5017. https://doi.org/10.3390/s19225017
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