• Journal of Positioning, Navigation, and Timing
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• v.12 no.2
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• pp.141-148
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• 2023

In this paper, impacts of tropospheric delay gradient correction on PPP positioning performance were analyzed. A correction for tropospheric delay error due to the gradient was created and applied using external data, and reference station data were collected on a sunny day and a rainy day to analyze the GPS only dual-frequency PPP positioning results. As a result, on the sunny day, the convergence time was about 35 minutes and the final 3D position error was 10 cm, regardless of whether the correction for the tropospheric delay error by the gradient was applied. On the other hand, on the rainy day, the 3D position error converges only when the correction was applied, and the convergence time was about 34 minutes. Furthermore, the final 3D position error was improved from 30 cm to 10 cm. In addition, the analysis of the PPP by reference station location on the rainy day showed that the PPP positioning performance was improved when the correction was applied to a user located in an area where the weather changes.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.1
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• pp.33-41
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• 2015

Compact Network Real-Time Kinematic (RTK) is a method that combines compact RTK and network RTK, and it can effectively reduce the time and spatial de-correlation errors. A network RTK user receives multiple correction information generated from reference stations that constitute a network, calculates correction information that is appropriate for one's own position through a proper combination method, and uses the information for the estimation of the position. This combination method is classified depending on the method for modeling the GPS error elements included in correction information, and the user position accuracy is affected by the accuracy of this modeling. Among the GPS error elements included in correction information, tropospheric delay is generally eliminated using a tropospheric model, and a combination method is then applied. In the case of a tropospheric model, the estimation accuracy varies depending on the meteorological condition, and thus eliminating the tropospheric delay of correction information using a tropospheric model is limited to a certain extent. In this study, correction information modeling accuracy performances were compared focusing on the Low-Order Surface Model (LSM), which models the GPS error elements included in correction information using a low-order surface, and a modified LSM method that considers tropospheric delay characteristics depending on altitude. Both of the two methods model GPS error elements in relation to altitude, but the second method reflects the characteristics of actual tropospheric delay depending on altitude. In this study, the final residual errors of user measurements were compared and analyzed using the correction information generated by the various methods mentioned above. For the performance comparison and analysis, various GPS actual measurement data were collected. The results indicated that the modified LSM method that considers actual tropospheric characteristics showed improved performance in terms of user measurement residual error and position domain residual error.

• Journal of Advanced Navigation Technology
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• v.20 no.1
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• pp.23-28
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• 2016

In this paper, we verified accuracy of the satellite based augmentation system (SBAS) tropospheric delay correction model for the Korean region. We employed the precise data of the tropospheric zenith path delay (ZPD) which is provided by the international GNSS service (IGS). In addition, we compared the verification results with that of the Saastamoinen model and the Hopfield model. Consequently, the bias residual error of the SBAS tropospheric delay correction model is about 50 mm, whereas the Saastamoinen model and the Hopfield model are more accurate. This residual error by the tropospheric delay model can affect the SBAS user position accuracy, but there is no problem in SBAS accuracy requirement. If we modified the meteorological parameters for SBAS tropospheric model to appropriate in Korean weather environment, we can provide better SBAS service to the Korean user.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.2
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• pp.163-170
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• 2016

Tropospheric delay is one of the largest error source in pseudolite navigation system. Because a pseudolite is installed on the ground and transmits its signal to a user in the air or on the ground, the conventional tropospheric delay model developed for a satellite navigation doesn't work properly. In this paper, performance analysis of several pseudolite tropospheric delay models has been done using meteorological data. Based on the result, a new compensation method for Hopfield model has been proposed.

• 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.

• Atmosphere
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• v.20 no.4
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• pp.399-414
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• 2010

Sand and dust storm in East Asia, so called Asian dust, is a seasonal meteorological phenomenon. Mostly in spring, dust particles blown into atmosphere in the arid area over northern China desert and Manchuria are transported to East Asia by prevailing flows. An Asian dust event occurred on 6-8 May 2007 is chosen to investigate how sensitive the Asian dust transport forecast to the initial condition uncertainties and to interpret the characteristics of sensitivity structures from the viewpoint of dynamics and predictability. To investigate the forecast sensitivities to the initial condition, adjoint sensitivities that calculate gradient of the forecast aspect (i.e., response function) with respect to the initial condition are used. The forecast aspects relevant to Asian dust transports are dry energy forecast error and lower tropospheric pressure forecast error. The results show that the sensitive regions for the dry energy forecast error and the lower tropospheric pressure forecast error are initially located in the vicinity of the trough and then propagate eastward as the surface low system moves eastward. The vertical structures of the adjoint sensitivities for the dry energy forecast error are upshear tilted structures, which are typical adjoint sensitivity structures for extratropical cyclones. Energy distribution of singular vectors also show very similar structures with the adjoint sensitivities for the dry energy forecast error. The adjoint sensitivities of the lower tropospheric pressure forecast error with respect to the relative vorticity show that the accurate forecast of the trough (or relative vorticity) location and intensity is essential to have better forecasts of the Asian dust event. Forecast error for the atmospheric circulation during the dust event is reduced 62.8% by extracting properly weighted adjoint sensitivity perturbations from the initial state. Linearity assumption holds generally well for this case. Dynamics of the Asian dust transport is closely associated with predictability of it, and the improvement in the overall forecast by the adjoint sensitivity perturbations implies that adjoint sensitivities would be beneficial in improving the forecast of Asian dust events.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.271-278
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• 2021

In this paper, a tropospheric delay error was calculated by using meteorological data collect from weather station and Saastamoinen model, and an empirical variogram of the tropospheric delay in the Korean peninsula was estimated. In order to estimate the empirical variogram of the tropospheric delay according to weather condition, sunny day, rainy day, and typhoon day were selected as analysis days. Analysis results show that a maximum correlation range of the empirical variogram on sunny day was about 560 km because there is overall trend of the tropospheric delay. On the other hand, the maximum correlation range of the empirical variogram on rainy was about 150 km because the regional variation was large. Although there is regional variation when the typhoon exists, there is a trend of the tropospheric delay due to a movement of the typhoon. Therefore, the maximum correlation range of the empirical variogram on typhoon day was about 280 km which is between sunny and rainy day.

• Journal of Positioning, Navigation, and Timing
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• v.2 no.1
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• pp.49-57
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• 2013

When pseudolite navigation system is applied to wide area, the tropospheric delay is the main error factor. In this study, we experimentally compared and analyzed the performance of the conventional pseudolite tropospheric delay models. The integration method using radiosonde meteorological data was suggested to derive the reference value for the comparison and analysis. Flight tests were carried out to analyze the performance of the tropospheric delay models according to the elevation angle and distance conditions between the user receiver and the pseudolite. As the results of this study, we provided the basis for the choice of tropospheric delay model appropriate to the relative location characteristics of the pseudolite and the user.

• Journal of Navigation and Port Research
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• v.40 no.5
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• pp.265-270
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• 2016

Extreme tropospheric anomalies such as typhoons or regional torrential rain can degrade positioning accuracy of the GPS signal. It becomes one of the main error terms affecting high-precision positioning solutions in network RTK. This paper proposed a detection algorithm to be used during atmospheric anomalies in order to detect the tropospheric irregularities that can degrade the quality of correction data due to network errors caused by inhomogeneous atmospheric conditions between multi-reference stations. It uses an atmospheric grid that consists of four meteorological stations and estimates the troposphere zenith total delay difference at a low performance point in an atmospheric grid. AWS (automatic weather station) meteorological data can be applied to the proposed tropospheric anomaly detection algorithm when there are different atmospheric conditions between the stations. The concept of probability density distribution of the delta troposphere slant delay was proposed for the threshold determination.

• Journal of the Korean earth science society
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• v.38 no.5
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• pp.345-356
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• 2017

It is important to understand the variability of tropospheric ozone since it is both a major pollutant affecting human health and a greenhouse gas influencing global climate. We analyze the characteristics of East Asia tropospheric ozone simulated in a chemistry-climate model. We use a global chemical transport model, driven by the prescribed meteorological fields from an air-sea coupled climate model simulation. Compared with observed data, the ozone simulation shows differences in distribution and concentration levels; in the vicinity of the Korean Peninsula, a large error occurred in summer. Our analysis reveals that this bias is mainly due to the difference in atmospheric circulation, as the anomalous southerly winds lead to the decrease in tropospheric ozone in this region. In addition, observational data have shown that the western North Pacific subtropical high (WNPSH) reduces tropospheric ozone across the southern China/Korean Peninsula/Japan region. In the model, the ozone changes associated with WNPSH are shifted westward relative to the observations. Our findings suggest that the variations in WNPSH should be considered in predicting tropospheric ozone concentrations.