• Title, Summary, Keyword: Tropospheric Delay Irregularity

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An Analysis for Irregularity of Tropospheric Delay due to Local Weather Change Effects on Network RTK (지역적 기상 차이에 의한 대류권 지연 변칙이 네트워크 RTK 환경에 미치는 영향 분석)

  • Han, Younghoon;Shin, Mi Young;Ko, Jaeyoung;Cho, Deuk Jae
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.63 no.12
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    • pp.1690-1696
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    • 2014
  • Network RTK generates spatial corrections by using differenced measurements from reference stations in the network, and the corrections are then provided to a rover. The rover, generally, uses linear interpolation, which assumes that the corrections at each reference station are spatially correlated, to obtain a precise correction of its location. However, an irregularity of the tropospheric delay is a real-world factor that violates this assumption. Tropospheric delay is a result of weather conditions, such as humidity, temperature and pressure, and it can cause spatial decorrelation when there are changes in the local climate. In this paper, we have defined the non-linear characteristics of the tropospheric delay between reference stations or user within a region as the "irregularity of tropospheric delay". Such an irregularity can negatively impact the network RTK performance. Therefore, we analyze the influence of the irregularity of tropospheric delay in network RTK based on meteorological data.

Effect of Tropospheric Delay Irregularity in Network RTK Environment (기준국 간 대류권 지연 변칙이 네트워크 RTK에 미치는 영향)

  • Han, Younghoon;Ko, Jaeyoung;Shin, Mi-Young;Cho, Deuk-Jae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.11
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    • pp.2569-2575
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    • 2015
  • Network RTK generally uses a linear interpolation method by using the corrections from reference stations. This minimizes the spatial decorrelation error caused by the increase of distance between the reference station's baseline and user's baseline. However, tropospheric delay, a function of the meteorological data can cause a spatial decorrelation characteristic among reference stations within a network by local meteorological difference. A non-linear characteristic of tropospheric delay can deteriorate Network RTK performance. In this paper, the modeling of tropospheric delay irregularity is made from the data when the typhoon is occurred. By using this modeling, analyzing the effect of meteorological difference between reference stations on correction is performed. Finally, we analyze an effect of non-linear characteristics of tropospheric delay among reference stations to Network RTK user.

Tropospheric Anomaly Detection in Multi-Reference Stations Environment during Localized Atmospheric Conditions-(2) : Analytic Results of Anomaly Detection Algorithm

  • Yoo, Yun-Ja
    • Journal of Navigation and Port Research
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    • v.40 no.5
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    • pp.271-278
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    • 2016
  • Localized atmospheric conditions between multi-reference stations can bring the tropospheric delay irregularity that becomes an error terms affecting positioning accuracy in network RTK environment. Imbalanced network error can affect the network solutions and it can corrupt the entire network solution and degrade the correction accuracy. If an anomaly could be detected before the correction message was generated, it is possible to eliminate the anomalous satellite that can cause degradation of the network solution during the tropospheric delay anomaly. An atmospheric grid that consists of four meteorological stations was used to detect an inhomogeneous weather conditions and tropospheric anomaly applied AWSs (automatic weather stations) meteorological data. The threshold of anomaly detection algorithm was determined based on the statistical weather data of AWSs for 5 years in an atmospheric grid. From the analytic results of anomaly detection algorithm it showed that the proposed algorithm can detect an anomalous satellite with an anomaly flag generation caused tropospheric delay anomaly during localized atmospheric conditions between stations. It was shown that the different precipitation condition between stations is the main factor affecting tropospheric anomalies.