• 전기학회논문지
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• 제63권12호
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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.

• 한국정보통신학회논문지
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• 제19권11호
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• pp.2569-2575
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• 2015

네트워크 RTK는 네트워크를 형성하는 다수의 기준국의 보정정보를 사용자 위치에 맞게 보간하여 사용함으로써 기준국과 사용자 간 기저선 거리 증가에 따른 공간이격 오차를 최소화 한다. 하지만 대류권 지연은 기상의 함수로 국지적인 기상변화를 원인으로 사용자와 네트워크 내 기준국 간 대류권 지연에 비선형 특성을 발생시킬 수 있으며, 이는 네트워크 RTK 성능을 저하시킬 수 있다. 따라서 본 논문에서는 태풍이 있던 날의 데이터를 기반으로 대류권 지연 변칙 사례를 모델링하고, 이를 이용하여 기준국 간 기상차이가 기준국에서 생성하는 보정정보에 미치는 영향을 분석한다. 또한, 기준국 간 대류권 지연의 비선형성이 네트워크 RTK 사용자에게 미치는 영향을 분석한다.

• 한국항해항만학회지
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• 제40권5호
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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.