• Journal of Astronomy and Space Sciences
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• v.35 no.4
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• pp.243-252
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• 2018

In a satellite gravimetry mission similar to GRACE, the precision of inter-satellite ranging is one of the key factors affecting the quality of gravity field recovery. In this paper, the impact of ranging precision on the accuracy of recovered geopotential coefficients is analyzed. Simulated precise orbit determination (POD) data and inter-satellite range data of formation-flying satellites containing white noise were generated, and geopotential coefficients were recovered from these simulated data sets using the crude acceleration approach. The accuracy of the recovered coefficients was quantitatively compared between data sets encompassing different ranging precisions. From this analysis, a rough prediction of the accuracy of geopotential coefficients could be obtained from the hypothetical mission. For a given POD precision, a ranging measurement precision that matches the POD precision was determined. Since the purpose of adopting inter-satellite ranging in a gravimetry mission is to overcome the imprecision of determining orbits, ranging measurements should be more precise than POD. For that reason, it can be concluded that this critical ranging precision matching the POD precision can serve as the minimum precision requirement for an on-board ranging device. Although the result obtained herein is about a very particular case, this methodology can also be applied in cases where different parameters are used.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.327-332
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• 2006

In airborne gravimetry, there are two data streams. One is the specific force measured by an air/sea gravimeter or accelerometers, the other is kinematic acceleration measured by DGPS. And the difference of them provides the gravity disturbance information. To satisfy the requirement of most applications, an accuracy of 1mGal $(1mCal=10^{-5}m/s^{2})$ with a spatial resolution of 1km is the aim of current airborne gravimetry. There are two different methods to derive the kinematic acceleration. The generally used method is to differentiate the position twice, and the position can be calculated by commercial DGPS software. The main defect of this method is that integer ambiguities need to be fixed to get the precise position solution, but it's not a trivial thing for long base line. And to fix integer ambiguities, the noisier iono-free measurement is used. When differentiation is applied, noise is amplified and will influence the accuracy of acceleration. The other method is to get carrier phase acceleration by differentiate the carrier phase first, and then using the acceleration of GPS satellite to derive the vehicle acceleration. The main advantages include that fixing integer ambiguities is not needed anymore, position can be relaxed to about 10 meters, and smoother acceleration can be got since iono-free measurement is not needed. In some literatures, it's considered that the dynamic performance of the second method is inferior to that of the first. Through analysis, it is found that the performance degradation in dynamic environment results from the simplification of the GPS carrier phase observable model. And an iterative algorithm is presented to compensate the model error. Using a dynamic GPS data from an aeromagnetic survey, the importance of this compensation is showed at last.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.467-467
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• 2015

Sustainable water resource management requires the assessment of hydrological variability in response to climate fluctuations and anthropogenic activities. Determining quantitative estimates of water balance and total basin discharge are of utmost importance to understand the variations within a basin. Hard-to-reach areas with few infrastructures, coupled with lengthy administrative procedures makes in-situ data collection and water management processes very difficult and unreliable. In this study, the hydrological behavior of Lake Chad whose extent, extreme climatic and environmental conditions make it difficult to collect field observations was examined. During a 10 year period [January 2003 to December 2013], dataset from space-borne and global hydrological models observations were analyzed. Terrestial water storage (TWS) data retrieved from Gravity Recovery and Climate Experiment (GRACE), lake level variations from Satellite altimetry, water fluxes and soil moisture from Global Land Data Assimilation System (GLDAS) were used for this study. Furthermore, we combined altimetry lake volume with TWS over the lake drainage basin to estimate groundwater and soil moisture variations. This will be validated with groundwater estimates from WaterGAP Global Hydrology Model (WGHM) outputs. TWS showed similar variation patterns Lake water level as expected. The TWS in the basin area is governed by the lake's surface water. As expected, rainfall from GLDAS precedes GRACE TWS with a phase lag of about 1 month. Estimates of groundwater and soil moisture content volume changes derived by combining altimetric Lake Volume with TWS over the drainage basin are ongoing. Results obtained shall be compared with WaterGap Hydrology Model (WGHM) groundwater estimate outputs.