Literature DB >> 32121278

Asynchronous RTK Method for Detecting the Stability of the Reference Station in GNSS Deformation Monitoring.

Yuan Du1,2, Guanwen Huang1, Qin Zhang1, Yang Gao2, Yuting Gao2.   

Abstract

The real-time kinematic (RTK) positioning technique of global navigation satellite systems (GNSS) has been widely used for deformation monitoring in the past several decades. The RTK technique can provide relative displacements in a local reference frame defined by a highly stable reference station. However, the traditional RTK solution does not account for reference stations that experience displacement. This presents a challenge for establishing a near real-time GNSS monitoring system, as since the displacement of a reference station can be easily misinterpreted as a sign of rapid movement at the monitoring station. In this study, based on the reference observations in different time domains, asynchronous and synchronous RTK are proposed and applied together to address this issue, providing more reliable displacement information. Using the asynchronously generated time difference of a reference frame, the proposed approach can detect whether a measured displacement has occurred in the reference or the monitoring station in the current epoch. This allows for the separation of reference station movements from monitoring station movements. The results based on both simulated and landslide monitoring data demonstrate that the proposed method can provide reliable displacement determinations, which are critical in deformation monitoring applications, such as the early warning of landslides.

Entities:  

Keywords:  GNSS real-time kinematic positioning; asynchronous real-time kinematic positioning; reference station; stability; synchronous real-time kinematic positioning

Year:  2020        PMID: 32121278     DOI: 10.3390/s20051320

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  2 in total

1.  An Early Warning Intelligent Algorithm System for Forest Resource Management and Monitoring.

Authors:  Liheng He; Tingru Zhu; Meng Lv
Journal:  Comput Intell Neurosci       Date:  2022-10-11

2.  Correlation between Acoustic Emission Behaviour and Dynamics Model during Three-Stage Deformation Process of Soil Landslide.

Authors:  Lizheng Deng; Hongyong Yuan; Jianguo Chen; Zhanhui Sun; Ming Fu; Fei Wang; Shuan Yan; Kaiyuan Li; Miaomiao Yu; Tao Chen
Journal:  Sensors (Basel)       Date:  2021-03-29       Impact factor: 3.576

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.