In single-frequency precise-point positioning of a satellite,ionosphere delay is one of the most important factors impacting the accuracy. Because of the instability of the ionosphere and uncertainty of its physical p...In single-frequency precise-point positioning of a satellite,ionosphere delay is one of the most important factors impacting the accuracy. Because of the instability of the ionosphere and uncertainty of its physical properties, the positioning accuracy is seriously limited when using a precision-limited model for correction. In order to reduce the error, we propose to introduce some ionosphere parameter for real-time ionosphere-delay estimation by applying various mapping functions. Through calculation with data from the IGS（ International GPS Service） tracking station and comparison among results of using several different models and mapping functions, the feasibility and effectiveness of the new method are verified.展开更多
For a scintillating-fiber array fast-neutron radiography system,a point-spread-function computing model was introduced,and the simulation code was developed. The results of calculation show that fast-neutron radiograp...For a scintillating-fiber array fast-neutron radiography system,a point-spread-function computing model was introduced,and the simulation code was developed. The results of calculation show that fast-neutron radiographs vary with the size of fast neutron sources,the size of fiber cross-section and the imaging geometry. The results suggest that the following qualifications are helpful for a good point spread function: The cross-section of scintillating fibers not greater than 200 μm×200 μm,the size of neutron source as small as a few millimeters,the distance between the source and the scintillating fiber array greater than 1 m,and inspected samples placed as close as possible to the array. The results give suggestions not only to experiment considerations but also to the estimation of spatial resolution for a specific system.展开更多
提出了一种在Bayes概率统计框架下的混合Bayes超分辨率重建算法,该算法采用Huber马尔可夫随机场(Huber Markov random field,HMRF)模型对理想图像进行先验建模,可以较好地突出重建图像的不连续边缘特征信息。实验结果表明,该算法克服了...提出了一种在Bayes概率统计框架下的混合Bayes超分辨率重建算法,该算法采用Huber马尔可夫随机场(Huber Markov random field,HMRF)模型对理想图像进行先验建模,可以较好地突出重建图像的不连续边缘特征信息。实验结果表明,该算法克服了极大后验概率估计(maximum a posteriori,MAP)算法中的若干缺陷,取得了良好的重建结果,图像边缘特征清晰,纹理信息突出。展开更多
基金supported by the National Natural Science Foundation of China(40902081,40774001,40841021)
文摘In single-frequency precise-point positioning of a satellite,ionosphere delay is one of the most important factors impacting the accuracy. Because of the instability of the ionosphere and uncertainty of its physical properties, the positioning accuracy is seriously limited when using a precision-limited model for correction. In order to reduce the error, we propose to introduce some ionosphere parameter for real-time ionosphere-delay estimation by applying various mapping functions. Through calculation with data from the IGS（ International GPS Service） tracking station and comparison among results of using several different models and mapping functions, the feasibility and effectiveness of the new method are verified.
基金Supported by the Foundation of Double-Hundred Talents of China Academy of Engineering Physics (Grant No. 2004R0301)
文摘For a scintillating-fiber array fast-neutron radiography system,a point-spread-function computing model was introduced,and the simulation code was developed. The results of calculation show that fast-neutron radiographs vary with the size of fast neutron sources,the size of fiber cross-section and the imaging geometry. The results suggest that the following qualifications are helpful for a good point spread function: The cross-section of scintillating fibers not greater than 200 μm×200 μm,the size of neutron source as small as a few millimeters,the distance between the source and the scintillating fiber array greater than 1 m,and inspected samples placed as close as possible to the array. The results give suggestions not only to experiment considerations but also to the estimation of spatial resolution for a specific system.
基金国家高技术研究发展计划(863)(the National High-Tech Research and Development Plan of China under Grant No.2006AA012324)航空基金(the Aeronautical Science Foundation No.20060853010)高等院校博士学科点专项科研基金(the China Specialized Research Fundfor the Doctoral Program of Higher Education under Grant No.20040699034)
文摘提出了一种在Bayes概率统计框架下的混合Bayes超分辨率重建算法,该算法采用Huber马尔可夫随机场(Huber Markov random field,HMRF)模型对理想图像进行先验建模,可以较好地突出重建图像的不连续边缘特征信息。实验结果表明,该算法克服了极大后验概率估计(maximum a posteriori,MAP)算法中的若干缺陷,取得了良好的重建结果,图像边缘特征清晰,纹理信息突出。
