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Qile Zhao Jing Guo Zhigang Hu Chuang Shi Jingnan Liu Hua Cai Xianglin Liu 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2011
The GRACE (Gravity Recovery And Climate Experiment) monthly gravity models have been independently produced and published by several research institutions, such as Center for Space Research (CSR), GeoForschungsZentrum (GFZ), Jet Propulsion Laboratory (JPL), Centre National d’Etudes Spatiales (CNES) and Delft Institute of Earth Observation and Space Systems (DEOS). According to their processing standards, above institutions use the traditional variational approach except that the DEOS exploits the acceleration approach. The background force models employed are rather similar. The produced gravity field models generally agree with one another in the spatial pattern. However, there are some discrepancies in the gravity signal amplitude between solutions produced by different institutions. In particular, 10%–30% signal amplitude differences in some river basins can be observed. In this paper, we implemented a variant of the traditional variational approach and computed two sets of monthly gravity field solutions using the data from January 2005 to December 2006. The input data are K-band range-rates (KBRR) and kinematic orbits of GRACE satellites. The main difference in the production of our two types of models is how to deal with nuisance parameters. This type of parameters is necessary to absorb low-frequency errors in the data, which are mainly the aliasing and instrument errors. One way is to remove the nuisance parameters before estimating the geopotential coefficients, called NPARB approach in the paper. The other way is to estimate the nuisance parameters and geopotential coefficients simultaneously, called NPESS approach. These two types of solutions mainly differ in geopotential coefficients from degree 2 to 5. This can be explained by the fact that the nuisance parameters and the gravity field coefficients are highly correlated, particularly at low degrees. We compare these solutions with the official and published ones by means of spectral analysis. It is found that our solutions are, in general, consistent with others in the spatial pattern. The water storage variations of the Amazon, Chari and Ganges river basins have also been computed. The variations computed with the NPARB approach are closer to those produced by JPL and DEOS solutions, while the variations produced with the NPESS approach are in good agreement with those produced by the CSR and GFZ solutions. A simulation study is implemented with considering realistic noise and low-frequency error. The two approaches are used to recover the true model. The NPESS solution appears closer to the true one. Therefore we are inclined to estimate the nuisance parameters simultaneously with the geopential coefficients. 相似文献
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可靠性设计优化(RBDO)在航空航天等领域已经被广泛应用,具有显著提高可靠性的效果;然而它包含两个迭代循环-总体优化循环和可靠性分析循环,双循环求解方法效率低下甚至难以承受。本文提出一种可以提高可靠性设计优化求解效率的方法-球空间设计法,该方法可以方便地表达搜索区域,最大可能失效点可以从极值点处精确获取;同时,该方法可以将总体优化以及可靠性分析同步进行。本文所提出的球空间法的有效性将通过2个算例进行测试,测试结果表明该方法不仅精度与同类方法持平,求解效率有明显提升,它将会对提高航空航天装备如卫星、火箭、飞行器等产品的可靠性提供更为有效的方法和技术支持。 相似文献
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