• 한국측량학회지
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• 제20권2호
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• pp.215-222
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• 2002

As the GPS signals propagate from the GPS satellites to the receivers on the ground, they are delayed by the atmosphere. The tropospheric delay consists of two components. The hydrostatic (or "dry") component that is dependent on the dry air gasses in the atmosphere and accounts for approximately 90% of the delay. And the "wet" component that depends on the moisture content of the atmosphere and accounts for the remaining effect of the delay. The Zenith Hydrostatic Delay (ZHD) can be calculated from the local surface pressure. The Total Zenith Delay (TZD) will be estimated and the wet component extracted later. Integrated water Vapor (IWV) gives the total amount of water vapor that a signal from the zenith direction would encounter. Precipitable Water Vapor (PWV) is the IWV scaled by the density of water. The quality of this PWV has been verified by comparison with radiosonde data(at Osan). We processed data for JULY 2 and JULY 14, 1999 from four stations(Cheju, Kwangju, Suwon, Daegu). We found the coincidence between PWV of the estimations using GPS and PWV of pressing the radiosonde data. The average of the difference between PWV using GPS and PWV using radiosonde was 3.77 mm(Std. ＝ $\pm$0.013 mm) and 2.70 mm(Std. = $\pm$0.0011 mm) at Suwon & Kwangju.

• 전자진흥
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• 제10권6호
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• pp.129-138
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• 1990

• 천문학회보
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• 제16권
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• pp.4.2-5
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• 1991

• 월간경쟁저널
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• 36호
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• pp.49-54
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• 1998

• 한국항해항만학회지
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• 제40권5호
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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.

• 항공우주산업기술동향
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• 제8권2호
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• pp.46-53
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• 2010

이 논문에서는 위성항법시스템의 운영 현황과 개발 계획에 대하여 기술하였다. 미국의 GPS(Global Positioning System)와 러시아의 GLONASS(Global Navigation Satellite System), 유럽의 Galileo, 중국의 Beidou/Compsss, 그리고 일본의 QZSS(Quasi-Zenith Satellite System) 에 대하여 시스템의 구성과 운영 위성 상태에 대하여 기술하였으며, 각 시스템의 개발 계획과 현대화에 대하여 기술하였다.

• 한국항공운항학회지
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• 제15권1호
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• pp.11-17
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• 2007

One of the key elements for developing GNSS (Global Navigation Satellite Systems) is the comprehensive analysis of GNSS satellite orbit including the capabilities to generate precision navigation message. The orbit characteristics of Japan's own GNSS system, called QZSS (Quasi Zenith Satellite System) is analyzed and its navigation message, which includes orbit elements and correction terms, is investigated. QZSS-type orbit simulations were performed using a precision orbit integrator in order to analyze the effect of perturbation forces, e.g. gravity, Moon, Sun, etc., on the orbit variation. A preliminary algorithm for creating orbit element corrections was developed and its accuracy is evaluated with the simulation data.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.794-796
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• 2006

This study investigated the Brightness Temperature Difference threshold as criterion between aerosols and clouds in conjunction with radiative transfer model. Surface temperature is caused by a significant error over 50% in the BTD threshold. In addition, The BTD threshold contains the uncertainties about 20% due to the surface emissivity and 8% due to the satellite zenith angle. Therefore, we have composed the Look-up table for BTD between 11㎛and 12㎛ according to satellite zenith angle, surface temperature, and surface emissivity. The modified BTD show the enhanced signal, especially over bright surface such as desert in China. However, a weak aerosol signal over Ocean remains in the modified BTD.

• ETRI Journal
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• 제38권6호
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• pp.1172-1178
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• 2016

The atmospheric meteorology parameters of the earth, such as temperature, pressure, and humidity, strongly influence the propagation of signals in Global Navigation Satellite Systems (GNSSs). The propagation delays associated with GNSS signals can be modeled and explained based on the atmospheric temperature, pressure, and humidity, as well as the locations of the satellites and receivers. In this paper, we propose an optimized and simplified low cost GNSS base weather station that can be used to provide a global estimate of the integrated water vapor value. Our algorithm can be used to measure the zenith tropospheric delay based on the measured propagation delays in the received signals. We also present the results of the data measurements performed at our station located in the Tlemcen region of Algeria.

• 아시안잔디학회지
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• 제18권4호
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• pp.211-219
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• 2004

Transgenic zoysiagrass (Zoysia japonica cv. Zenith) plants have been obtained by particle bombardment of embryogenic callus with the plasmid pSMABuba, which contains hygromycin resistance (hpt) and bialaphos resistance (bar) genes. Parameters on DNA delivery efficiency of the particle bombardment were partially optimized using transient expression assay of a chimeric $\beta-glucuronidase$(gusA) gene driven by the CaMV 35S promoter. Stably transfarmed zoysiagrass plants were recovered with a selection scheme using hygromycin. Transgenic zoysiagrass plants were confirmed by PCR analysis with specific primer for bar gene. Expression of the transgene in transformed zoysiagrass plants was demonstrated by Reverse transcriptase (RT)-PCR analysis. All the tested transgenic plants showed herbicide BastaR resistance at the field application rate of $0.1\%-0.3\%$.